Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil Data Analytics using Machine Learning Techniques – A Survey

Food security is the most basic need with any individual all over the globe. With food security we can reduce malnutrition in children, who are the backbone of nation’s development. To achieve this using machine learning techniques in agriculture domain is the new beginning. Machine learning techniques successfully implemented in innumerable domains, now entered in agriculture. Machine learning techniques establishes a novel way in data processing and data analytics, producing good results with larger data. In this work we carried out survey on machine learning technique’s role in agriculture domain and challenges involved in it. We examined the models developed based on agricultural soil. In addition, we analyzed the associations between soil nutrients, which help in crop yield. These results specify that the accuracy of the model is more with ensemble methods.
Digital Transformation in the Diagnostics and Therapy of Cardiovascular Diseases: Comprehensive Literature Review

Background The digital transformation of our health care system has experienced a clear shift in the last few years due to political, medical, and technical innovations and reorganization. In particular, the cardiovascular field has undergone a significant change, with new broad perspectives in terms of optimized treatment strategies for patients nowadays. Objective After a short historical introduction, this comprehensive literature review aimed to provide a detailed overview of the scientific evidence regarding digitalization in the diagnostics and therapy of cardiovascular diseases (CVDs). Methods We performed an extensive literature search of the PubMed database and included all related articles that were published as of March 2022. Of the 3021 studies identified, 1639 (54.25%) studies were selected for a structured analysis and presentation (original articles: n=1273, 77.67%; reviews or comments: n=366, 22.33%). In addition to studies on CVDs in general, 829 studies could be assigned to a specific CVD with a diagnostic and therapeutic approach. For data presentation, all 829 publications were grouped into 6 categories of CVDs. Results Evidence-based innovations in the cardiovascular field cover a wide medical spectrum, starting from the diagnosis of congenital heart diseases or arrhythmias and overoptimized workflows in the emergency care setting of acute myocardial infarction to telemedical care for patients having chronic diseases such as heart failure, coronary artery disease, or hypertension. The use of smartphones and wearables as well as the integration of artificial intelligence provides important tools for location-independent medical care and the prevention of adverse events. Conclusions Digital transformation has opened up multiple new perspectives in the cardiovascular field, with rapidly expanding scientific evidence. Beyond important improvements in terms of patient care, these innovations are also capable of reducing costs for our health care system. In the next few years, digital transformation will continue to revolutionize the field of cardiovascular medicine and broaden our medical and scientific horizons.
Particle fluxes from short-term sediment trap deployments in late summer in the southern Kara Sea

In September 1999, two short-term moorings with cylindrical sediment traps were deployed to collect sinking particles in bottom waters off the Ob and Yenisei river mouths. Samples were studied for their bulk composition, pigments, phytoplankton, microzooplankton, faecal material, amino acids, hexosamines, fatty acids and sterols, and compared to suspended matter and surface sediments in order to obtain information about the nature and cycling of particulate matter in the water column. Plankton counts and organic biogeochemical analyses of sinking particles of the Ob trap show that an ongoing plankton bloom has been sampled. During the twelve days of sampling we could observe a change of species distribution. Diatoms and copepods have been the dominating phytoand, respectively, zooplankters during the first phase of the trap deployment. Subsequently, other phytoplankters such as flagellates have become more important, and protozoa and larvaceans have become the dominating zooplankters. Biomarkers and amino acids indicate that the system has shifted from a phytoplankton to a more zooplankton dominated system in the second half of trap deployment. This may be an indication of (i) a propagating plankton bloom with its shift from primary to secondary producers or (ii) the intrusion of different species related to lateral transport in a hydrodynamically active environment. The Ob trap collected fresh surface-derived particulate matter, whereas particles from the Yenisei trap were more degraded and resembled deep water suspension. This material may partly have been derived from resuspended sediments.
WIRELESS POWER TRANSFER FOR UNDERWATER VEHICLES

Wireless power transfer (WPT) through magnetic resonance coupling (MRC) offers a safe and simple solution for underwater (UV) vehicles without being affected by water conductivity. Due to its ease of control in WPT systems, the most suitable topology is Serial-Serial (SS). In this study, square transmitting and receiving coils with dimensions of 40 cm - 40 cm were designed for 3.3 kW power transmission at 85 kHz. The design was studied in the air, pure water, and seawater environments. Three different cases were analyzed with ANSYS Maxwell 3D. The WPT system responded similarly in air and pure water environments. However, it was determined that the eddy current loss increased, the mutual inductance decreased, the coupling factor weakened, and the critical air gap decreased by about 0.2 cm in the seawater environment. The results showed that the WPT system's efficiency was similar for air and pure water but tolerably lower in the marine environment. Further, the health effects of the WPT design were examined through the ANSYS HFSS, in line with the IEEE standard and ICNIRP guidelines.
Nuevos nanocomposites grafeno/líquido iónico en matriz epoxi

En el presente trabajo se han preparado nanocomposites de matriz epoxi (RE) modificada mediante la adicion de particulas de grafeno 1 o 2 capas (PG) y mediante la adicion de PG y del liquido ionico tetrafluoroborato de 1-metil-3-octilimidazolio (LI). Se han preparado tambien dispersiones de LI con PG con el fin de observar su comportamiento como lubricante externo. Se han realizado ensayos de punzon sobre disco con el fin de estudiar la resistencia al desgaste adhesivo y abrasivo de las muestras. Se han estudiado los mecanismos de dano superficial mediante microscopia electronica de barrido y perfilometria optica, asi como las propiedades termicas de las nuevas dispersiones.
IoT-Driven Image Processing Framework for Accurate Skin Diseases Diagnosis and Classification

- Skin diseases affect millions worldwide, and accurate diagnosis and classification are critical for effective treatment. The Internet of Things (IoT) has emerged as a powerful technology that can be used to improve healthcare systems in recent years. This paper proposes an image processing framework based on IoT for accurate skin disease diagnosis and classification. To enable remote and real-time skin disease diagnosis, the proposed framework combines the capabilities of IoT devices, such as smartphones or wearable cameras
Search for heavy resonances decaying into WW in the final state in pp collisions at with the ATLAS detector

A search for neutral heavy resonances is performed in the WW → eνμν decay channel using pp collision data corresponding to an integrated luminosity of 36.1 fb−1, collected at a centre-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. No evidence of such heavy resonances is found. In the search for production via the quark–antiquark annihilation or gluon– gluon fusion process, upper limits on σX × B(X → WW ) as a function of the resonance mass are obtained in the mass range between 200 GeV and up to 5 TeV for various benchmark models: a Higgs-like scalar in different width scenarios, a two-Higgs-doublet model, a heavy vector triplet model, and a warped extra dimensions model. In the vector-boson fusion process, constraints are also obtained on these resonances, as well as on a Higgs boson in the Georgi–Machacek model and a heavy tensor particle coupling only to gauge bosons.
Locality Constraint Joint-Sparse and Weighted Low-Rank Based Hyperspectral Image Classification

In this paper, a spectral-spatial classification method based on locality constrained joint-sparse and weighted low-rank (LCJS-WLR) for homogeneous regions in hyperspectral image (HSI) which are extracted by superpixel segmentation is proposed. Pixels in a superpixel have similar spectral signatures and they are represented by joint atoms in a training dictionary, which means that coefficient matrix has joint-sparse and low-rank structure. In order to give higher weights to atoms whose spectral characteristics are similar to pixels inside superpixel, locality constraint is adopted to the joint-sparse term. Weighted low-rank representation is used to enhance low-rankness prop-erty of the data. The possible sparse noise terms are eliminated by adding a sparse noise regularization term. Experiments on a real hyperspectral data set point out that LCJS-WLR provides better classification performance than the methods under comparison.
Designing of Harmonics Filter for Radio Systems at 30–49 MHz

In this study, the design of low pass filter that will operate in the 30–49 MHz band and attenuate the 2nd and 3rd harmonics of the signals in the band is described. Its topology is Chebyshev and it is 11th-degree filter. The harmonic attenuation value of the designed filter is -60 dB. It is designed to handle 100 W RF(CW) power. It has been implemented and. Measurement result and simulation result were compared.
Aktieägarvärden i fokus : internationell påverkan på intressentrelationer genom förvärv och fusion

Sverige ar ett av de lander som paverkas mest av globaliseringen. En kraftig okning av utlandska direktinvesteringar och gransoverskridande forvarv och fusioner har forandrat det svenska naringslivet. Var femte svensk i naringslivet arbetar idag i ett utlandsagt foretag. Utlandska institutionella investerare star for runt en tredjedel av agandet pa Stockholmsborsen. Ett nytt satt att se pa foretagens mal och mening sags ha kommit till Sverige. Talet om aktieagarvarde ges utrymme i media och i foretagens kommunikation. Det satter aktieagarna i framsta rummet pa ett satt som ar annorlunda jamfort med ett svenskt intressentmodellsorienterat satt att se pa foretaget.Mot denna bakgrund studeras fyra svenska foretag som snabbt blir mer internationella genom forvarv och fusioner. I en hermeneutisk studie far vi genom kvalitativa och longitudinella fallstudier folja anstallda och chefer och se deras reaktioner pa de stora forandringar som internationaliseringen innebar for vardagslivet i organisationen. Lasaren erbjuds en explorativ och induktiv resa som ger en okad forstaelse for motet mellan det svenska och det globala och for vilken paverkan som sker pa svenska foretags relationer med sina nara intressenter.
Suitability of radio telemetry for monitoring two New Zealand frogs (Leiopelma archeyi and L. hamiltoni)

: The miniaturisation of very high frequency transmitters over the last 20 years has allowed researchers to use radio telemetry to study the movements and behaviours of increasingly smaller animals. However, the sensitive skin of many amphibians has continued to make fitting telemetry packages difficult. Here we describe the application of a waist-harness style radio telemetry package for use on two of New Zealand’s native terrestrial frogs ( Leiopelma archeyi and L. hamiltoni ). To determine if the harness design was suitable for field use, we conducted a laboratory trial on four captive L. hamiltoni . Individuals carried harnesses for up to 22 consecutive days without abrasions or changes in behaviour. After confirming the harness would not negatively impact captive individuals, we fitted harnesses to 20 L. hamiltoni in Te Pākeka/Maud Island Scientific Reserve, northern South Island. We tracked individuals for a maximum of 8 days and recaptured L. hamiltoni showed no signs of skin irritation or skin damage at the time of harness removal. We also tested harnesses on four L. archeyi within the Wharekirauponga area of the Coromandel Forest Park, northeastern North Island. We were able to track one L. archeyi for 7 days before locating the transmitter loose in leaf litter. The harness detached from two additional individuals, one within 24 hours of frog release and another 12 hours after release. We were unable to relocate one individual. Although the use of radio telemetry on leiopelmatids is not without difficulties, the observations collected during our field trials provide strong support that a waist-harness design is a suitable and effective method to conduct short-term radio telemetry on leiopelmatid frogs.
A Machine Learning Based Framework for Real-Time Detection and Mitigation of Sensor False Data Injection Cyber-Physical Attacks in Industrial Control Systems

In light of the advancement of the technologies used in industrial control systems, securing their operation has become crucial, primarily since their activity is consistently associated with integral elements related to the environment, the safety and health of people, the economy, and many others. This work presents a distributed, machine learning based attack detection and mitigation framework for sensor false data injection cyber-physical attacks in industrial control systems. It is developed using the system’s standard operational data and validated using a hybrid testbed of a reverse osmosis plant. A MATLAB/Simulink-based simulation model of the process validated with actual data from a local plant is used. The control system is implemented using Siemens S7-1200 programmable logic controllers with 200SP Distributed Input/Output modules. The proposed solution can be adopted in the existing industrial control systems and demonstrated effective performance in real-time detection and mitigation of actual cyber-physical attacks launched by compromising the communication links between the process and the programmable logic controllers.
Improved Moving Target Imaging Method for a Multichannel HRWS SAR System

The azimuth multichannel synthetic aperture radar (AMC-SAR) system makes possible simultaneous high-resolution and wide-swath (HRWS) Earth observation. The motion of moving targets illuminated by the AMC-SAR system will not only lead to the failure of signal reconstruction, resulting in false targets in the image, but also to the defocusing of the moving targets. These problems can be effectively addressed by the estimation of the moving target parameters and their compensation in the signal. The existing imaging methods focus on eliminating the impact of radial velocity on signal reconstruction and disregard the influence of other motion parameters. However, the radial acceleration, azimuth acceleration, and azimuth velocity of moving targets affect the accuracy of the signal reconstruction and focusing of the images. To eliminate the influence of target motion, this letter proposes a moving target imaging method. First, the proposed method transforms the problem of parameter estimation into the problem of phase error estimation. Second, the quadratic phase error (QPE) is accurately estimated via autofocus theory and compensated in the signal, improving the focusing of a moving target. Then, the linear phase error (LPE) is accurately estimated via subspace theory and compensated in the signal, improving the accuracy of signal reconstruction. The effectiveness of our proposed method is demonstrated through processing of simulated SAR data.
Hyperspectral Band Selection Based on Fuzzy C-means and Dingo Optimization Algorithm

Dimensionality reduction is necessary for hyperspectral image processing to reduce redundant information and improve classification accuracy and efficiency. Band selection is a dimensionality reduction method that selects a representative subset of bands from a hyperspectral band set according to certain rules. A novel band selection method based on fuzzy c-means (FCM) and dingo optimization algorithm (DOA) is proposed, which uses the FCM Algorithm to divide hyperspectral image into several subspaces and then uses the DOA to select representative bands within each subspace. The objective function of the optimization algorithm integrates the band information entropy and the redundancy of the band subsets. Three commonly used hyperspectral image datasets were used to test the proposed algorithm, and support vector machine was used to classify the selected bands. The results have shown that the proposed algorithm has high classification accuracy compared with other algorithms, which verifies the effectiveness of band selection.
Finite Element Time Domain Discretization of a Semiclassical Maxwell-Schrödinger Model of a Transmon Qubit

In superconducting circuit quantum computers, classical microwave pulses are used to control and measure the state of the qubits. The design of microwave pulses for these purposes typically use simple theoretical or numerical models that do not account for the self-consistent interactions of how the presence of the transmon modifies the applied microwave field. In this work, we present the formulation and finite element time domain discretization of a semiclassical Maxwell-Schrödinger model that can self-consistently characterize the interactions between a transmon and classical microwave pulses. Our numerical results demonstrate the validity of this approach for describing the central effects related to the control and measurement of the state of a transmon. In the future, our numerical method can be used to efficiently investigate a wider range of operating regimes than existing approaches are valid for to search for more effective control and measurement protocols.
Switchgrass Cost of Production: Data from On-Farm Trial, 2001-2005

Switchgrass is considered a potential commercial biomass feedstock but field scale production and production cost data have been limited. The costs of production incurred on ten commercial-sized fields in the northern Great Plains, between 2000 and 2005 have been reported in a scientific journal paper. This report provides the detailed information, in English metric units, that was used to conduct the economic analyses. The average annualized cost to produce and store switchgrass on these farms was $60 per ton of dry matter, which translates to an ethanol feedstock cost of about $0.66-0.75 per gallon of ethanol, depending upon the ultimate ethanol yield. I. Objectives and Methods The United States Department of Energy (DOE) designated switchgrass as a potential bioenergy feedstock because of its wide adaptability and high yields on marginal lands. But because switchgrass is not presently a commercial crop, the cost of production, and therefore the price that would bring forth commercial production, is conjectural. While there have been estimates of the cost of producing switchgrass (Walsh (1994), Duffy and Nanhou (2001)), they have been based on inferences from plot-level yields and engineering cost budgeting approaches. Because of this dearth of commercialscale cost information, DOE and the USDA's Agricultural Research Service funded a collaborative project with the University of Nebraska, to estimate commercial-scale production costs in the northern Great Plains, by contracting with collaborating farmers to produce the crop and report detailed records on costs. The on-farm studies were conducted on ten rainfed fields of 15-20 acres each, scattered from southern Nebraska up through South Dakota to northern North Dakota (see Figure 1 and Table 1.) The fields selected had characteristics that would have qualified them for the Conservation Reserve Program (CRP), and were typical of their surrounding geographical region. In this report, the fields are identified by the name of the nearest town. The sites are briefly described in Table 1. The Nebraska fields were established in 2000 and continued through 2004. The South Dakota and North Dakota fields were established in 2001, and continued through 2005. The Atkinson, NE, site changed size during the study. It consisted of two "pivot corners", the non-irrigated 4 A journal version of this report, in metric units, is to appear in BioEnergy Research, March, 2008. (Give full citation) 5 USDA-University of Nebraska Cooperative Agreements 58-5440-0-305 and 25-62240060-001, "Economic Evaluation of Switchgrass Grown as a Biomass Energy Crop in the Central and Northern Plains, USA. "
Optimization of the Aeroacoustics and Aerodynamics of a Wind Turbine Airfoil with Serrations Using Multi-Criteria Decision Making

With the growing demand for green energies and the increasingly stringent regulations on noise emission, improvement of the performance of wind turbines includes both power generation and noise emission. This paper presents a study of the aerodynamic and aeroacoustic performance of the tip airfoil of the National Renewable Energy Laboratory (NREL) phase VI wind turbine. Taguchi design and Grey grade are employed to optimize trailing edge serration plates over the S809 airfoil. The output is evaluated in the form of a compromise between increased aerodynamic performance and decreased trailing edge noise generation. The results show a reduction in the Sound Pressure Levels (SPL) for all configurations in the lower frequencies. All the considered configurations of the serration plate improve the Overall A-Weighted Sound Pressure Level (OASPL) and the force generation.
Implementation of Efficient Digit Recurrence Class of Division Algorithms

The basic elements of an electronic system are arithmetic operations. Arithmetic operations are the building block of any electronic application and algorithm is a sequence of instructions used to carry out calculations or solve problems. In spite of the fact that addition, subtraction, multiplication, and division are fundamental components of arithmetic implementation in the electronic system, the implementation of division has received far less attention than the implementation of the other arithmetic operations. The process of dividing two numbers using the method results in the production of a quotient in addition to a remainder. The implementation of division operations is highly challenging; thus, in this scenario, a complex method is employed to ensure successful implementation. To be successful, a system has to have a solid performance in the division circuit. In this body of work, the Restoring division and Non-restoring division algorithms, which fall under the category of Digit Recurrence Class, have been developed for unsigned integers with data sizes of 8 bit, 16 bit, and 32 bit using the Verilog HDL programming language. These algorithms are applicable to unsigned integers with data values of 8, 16, and 32 bits respectively. In each of these algorithms, the calculation takes place in one of three registers designated by the letters A, Q, or M.