Use Of Package Research Articles

Numerical Modeling of Tsunamis Generated by Subaerial, Partially Submerged, and Submarine Landslides

Using the existing two-dimensional experimental data and Open-source Fields Operation and Manipulation (OpenFOAM) software, this study performs a comprehensive comparative analysis of three types of landslide-generated tsunamis (subaerial, partially submerged, and submarine). The primary objective was to assess whether numerical simulations can accurately reproduce the experimental results of each type and to compare the predictive equations of the tsunami amplitudes derived from experimental and simulated data. The mesh size and dynamic viscosity parameters were initially optimized for a specific partially submerged landslide tsunami scenario and then applied across a broader range of experimental scenarios. Most of the simulated wave amplitudes remained within the 50% error margin, although significant discrepancies were observed between landslide types. When focusing on the crest amplitude of the first wave, the simulations of subaerial landslides least deviated from the experimental data, with a mean absolute percentage error of approximately 20%, versus approximately 40% for the partially submerged and submarine landslides. The predictive equations derived from the simulations closely matched those from the experimental data, confirming that OpenFOAM can effectively capture complex landslide–tsunami dynamics. Nonetheless, variations in the coefficients related to slope angles highlight the need for further calibration to enhance the simulation fidelity.

Development of an Algorithm for Determining the Class of an Obstacle in the Process of its Interaction with the Manipulator

The article discusses the problem of determining the nature of an obstacle using a force sensor for terrain mapping. Three classes of objects have been introduced: the first class is "static" obstacles, the second class is "moving" obstacles, the third class is "unstable" obstacles. To conduct experiments, a simulation system was built in the Gazebo modeling environment, including a manipulator with the ability to horizontally move a probe with a force sensor and a set of obstacles corresponding to three classes of obstacles. All experiments were carried out using the ROS framework, the Gazebo simulator and the Movelt manipulation software. Processing of signals from the force sensor showed that the sig­nals for the three classes of obstacles are different, which makes it possible to identify the class based on sensor readings. Based on the analysis of data received from the sensor, rules were formed that make it possible to determine the class of an obstacle during its interaction with the manipulator in real time. To determine the obstacle class, the values of the force sensor signals are considered, smoothed by the moving average method. According to the rules discussed in the article, an algorithm was developed to determine the class of obstacle, which was implemented in the Gazebo modeling environment. Testing of the algorithm showed the stability of its operation under the given experimental conditions. Successful determination of the obstacle class will allow one not only to construct a map of the area, but also to prevent damage to the device when exposed to a "static" object with excessive force. The presented approach can be expanded to narrower classes of obstacles that characterize objects that can be encountered by a mobile device when mapping a forest area.

Using Systems Engineering and Implementation Science to Design an Implementation Package for Preoperative Comprehensive Geriatric Assessment Among Older Adults Having Major Abdominal Surgery: Protocol for a 3-Phase Study.

Older Americans, a growing segment of the population, have an increasing need for surgical services, and they experience a disproportionate burden of postoperative complications compared to their younger counterparts. A preoperative comprehensive geriatric assessment (pCGA) is recommended to reduce risk and improve surgical care delivery for this population, which has been identified as vulnerable. The pCGA optimizes multiple chronic conditions and factors commonly overlooked in routine preoperative planning, including physical function, polypharmacy, nutrition, cognition, mental health, and social and environmental support. The pCGA has been shown to decrease postoperative morbidity, mortality, and length of stay in a variety of surgical specialties. Although national guidelines recommend the use of the pCGA, a paucity of strategic guidance for implementation limits its uptake to a few academic medical centers. By applying implementation science and human factors engineering methods, this study will provide the necessary evidence to optimize the implementation of the pCGA in a variety of health care settings. The purpose of this paper is to describe the study protocol to design an adaptable, user-centered pCGA implementation package for use among older adults before major abdominal surgery. This protocol uses systems engineering methods to develop, tailor, and pilot-test a user-centered pCGA implementation package, which can be adapted to community-based hospitals in preparation for a multisite implementation trial. The protocol is based upon the National Institutes of Health Stage Model for Behavioral Intervention Development and aligns with the goal to develop behavioral interventions with an eye to real-world implementation. In phase 1, we will use observation and interviews to map the pCGA process and identify system-based barriers and facilitators to its use among older adults undergoing major abdominal surgery. In phase 2, we will apply user-centered design methods, engaging health care providers, patients, and caregivers to co-design a pCGA implementation package. This package will be applicable to a diverse population of older patients undergoing major abdominal surgery at a large academic hospital and an affiliate community site. In phase 3, we will pilot-test and refine the pCGA implementation package in preparation for a future randomized controlled implementation-effectiveness trial. We anticipate that this study will take approximately 60 months (April 2023-March 2028). This study protocol will generate (1) a detailed process map of the pCGA; (2) an adaptable, user-centered pCGA implementation package ready for feasibility testing in a pilot trial; and (3) preliminary pilot data on the implementation and effectiveness of the package. We anticipate that these data will serve as the basis for future multisite hybrid implementation-effectiveness clinical trials of the pCGA in older adults undergoing major abdominal surgery. The expected results of this study will contribute to improving perioperative care processes for older adults before major abdominal surgery. DERR1-10.2196/59428.

Automation of the <i>Ad Hoc</i> Approach for Derandomization of Proteins: A Tutorial for Undergraduates in Molecular Sciences

Data analysis and manipulation software are vulnerable to user error during data processing and computations take considerable time when handling huge data and multiple repetitive tasks. These problems are usually mitigated by creating an app to repeat any given task reproducibly any number of times. This paper discusses the development of app that systematically automates the <i>ad hoc</i> approach for derandomization of proteins and, or peptides. Thirty second-year undergraduates with little-to-no prior knowledge of computer programming are (were) asked to create this app with modules that sequentially convert spectra from original units to molar extinction and subtract baseline spectrum from the resultant spectra, derandomize the spectra by removing suspected significant unfolded domains from them, concatenate the generated files to a single file in an acceptable format for structural analysis, process our group structural algorithm output files into a user-friendly format to ease data analysis. In addition, they are (were) asked to prepare protein solution, determine its concentration spectroscopically, collect circular dichroism measurements of the protein, derandomize the protein spectra, and determine the secondary structure of the resultant protein spectra with our structure algorithm. The assessment results demonstrated that the students could prepare samples for CD analysis, collect spectra of proteins, and create an app to automate the <i>ad hoc</i> approach. The hands-on activities enable students to acquire knowledge in basic programming and circular dichroism, CD spectroscopy.

3D-Animated Cartoon Instructional Package and Effective Teaching of Selected Topics in Financial Accounting in Pubic Secondary Schools, South-South, Nigeria

This study was carried out to determine the difference in students’ academic performance in financial accounting when taught using 3D-cartoon animation package and a conventional approach. The selected topics for the study include transaction analysis, accounting equation, cash book and ledger. The research design the researchers adopted for this study was quasi quasi-experimental method and the area of the study was South-South, Nigeria. The population of the study consisted of 242,052. The sample size was 192 and a purposive sampling technique was used for the study. The Financial Accounting Achievement Test (FAAT) was used to collect data for the study. The internal consistency index of .92 was obtained using test-retest. The data were analyzed using mean and standard deviation to answer research questions and ANCOVA to test the null hypotheses at .05 level of significance. Among other recommendations made was that the government should encourage schools to embrace the latest teaching strategies by way of providing the 3D instructional package for use in schools.

Food packaging films based on ionically crosslinked konjac glucomannan incorporating zein-pectin nanoparticle-stabilized corn germ oil-oregano oil Pickering emulsion.

This study addresses the limitations of konjac glucomannan (KGM) films in mechanical properties, hydrophobicity and antibacterial activities. For the first time, a zein-pectin nanoparticle-stabilized corn germ oil-oregano essential oil Pickering emulsion (ZPCEO) was incorporated into KGM, with the resulting film being further ionically crosslinked with Ca2+, Cu2+ or Fe3+. FTIR, SEM and EDS results showed that the metal ions were crosslinked with the hydroxyl and carbonyl groups of polysaccharides and uniformly distributed throughout the films (degree of crosslinking: Fe3+ > Cu2+ > Ca2+). Compared with pure KGM films, the ionic crosslinked ZPCEO/KGM (IL-ZPCEO/KGM) films have superior water resistance mechanical properties, and exhibit unique UV-blocking properties, antioxidant and antibacterial activities. The ZPCEO/KGM-Fe3+ film offered the best all-round properties, including the highest tensile strength, water resistance, UV-blocking capacity, and antimicrobial activity. Thus, ionic crosslinking of ZPCEO/KGM films can be applied to the preparation of food packaging for use in high humidity environments.

Anatomical and Clinical Characteristics of Scalp Acupuncture Systems: a Scoping Review and Synthesis.

Scalp acupuncture is a therapeutic procedure that involves inserting needles into the scalp to treat various medical conditions, including pain and neurological and psychological disorders. The inter-system variability of scalp acupuncture limits secondary analysis and evidence synthesis, delaying its inclusion into evidence-based healthcare policies and establishment as a treatment intervention recognized by Western medicine. This scoping review aimed to identify the range of scalp acupuncture systems, systematically collect and summarize information on their general, anatomical, and clinical characteristics, and build a framework for understanding scalp acupuncture systems. This review included all English-language publications on scalp acupuncture applied to treat any health condition in humans. Extensive searches were conducted across bibliographic databases, journals, trial registries, and supplementary sources. The detailed general, anatomical, and clinical application characteristics of 19 scalp acupuncture systems were extracted. Data were collected and analyzed using charting and image manipulation software. Framework synthesis was performed using the Standard International Acupuncture Nomenclature Scalp Acupuncture as an a priori framework. The review revealed that the heterogeneity related to scalp acupuncture methods can be attributed to the high variability among the theoretical bases of different systems, intersystem mismatch in anatomical locations of treatment points and areas on the scalp, and inconsistencies in the methods used for locating them. These discrepancies in anatomical and clinical features have limited the synthesis and development of a framework for scalp acupuncture. Discussion and agreement on the anatomical locations of scalp stimulation areas, identification of methods for precise positioning of acupuncture areas on the scalp, and further exploration of theoretical bases will aid in the standardization of scalp acupuncture and improve the quality of research in this area.

A Ketamine Package for Use in Emergency Cesarean Delivery When No Anesthetist is Available: An Analysis of 401 Consecutive OperationsAnesthesia and AnalgesiaAnesthesia and Analgesia

(Int J Gynecol Obstet. 2022;158:377–384) Average maternal mortality in low-income countries has been reported as 40 times higher than that of high-income countries. One contributing factor to this discrepancy is the shortage of surgical care either due to inaccessible resources or inaccessible clinicians such as anesthesiologists. There is a particularly noticeable gap in anesthesiology care, as most low-income countries do not have anesthesiology training programs, or the programs do not produce enough clinicians to fully staff what is needed. This study aimed to understand the implications of using ketamine as an anesthetic to support emergency surgical delivery if no anesthetist is available. Effectiveness and safety was evaluated through maternal and newborn outcomes. The primary outcome was maternal and infant survival, and the ability of ketamine to safely support cesarean deliveries (CD).

CFD SIMULATION AND VALIDATION FOR MIXING VENTILATION SCALED-DOWN EMPTY AIRCRAFT CABIN USING OPENFOAM

An investigation into the spread of the COVID-19 virus within a confined space including an aircraft cabin is essential in order to find out the mechanism. However, this is time-consuming and limited in scope, so a computational fluid dynamics (CFD) simulation is used instead. Therefore, a prior study and an appropriate choice of turbulence model are required before the simulation. The main objective of this study is to validate and evaluate the results predicted by the Open Source Field Operation and Manipulation (OpenFOAM) software through comparison with the experimental data from the literature which was conducted using particle image velocimetry (PIV) measurement. Three different Reynolds-averaged Navier-Stokes turbulence models were selected; Re-normalisation Group k - ɛ (RNG), Realizable k - ɛ (RLZ) and Low Reynold Number (LRN) to simulate a mixing ventilation system of a scaled-down model of empty aircraft cabin. In the RNG and LRN model cases, a fairly large circulation flows were observed on the right and left sides of the model representing the passenger area. The results were also evaluated quantitatively using the factor of two of observations (FAC2) for the velocity components and turbulent kinetic energy (TKE) with root mean square error (RMSE) for the former and normalised mean square errors (NMSE) for the latter. The simulation results showed that RNG and LRN are capable of predicting the flow field well. However, for TKE prediction LRN performed better than RNG which concluded that LRN is the suitable turbulence model in simulating flow fields in investigated case.

Dementia and mild cognitive impairment in the older prison population in England and Wales (DECISION): developing a dementia care training package for use in prisons

ABSTRACT The rising prevalence of dementia in the UK presents a public health and economic challenge. People over the age of 60 are the fastest growing age group in prison and the number of people in prison who experience dementia is rising. There is a lack of research focused on improving management and support for people in prison who may experience dementia, but growing awareness of the need for staff training in prisons to identify and support people showing symptoms of dementia. This paper reports the development of a theory and evidence-based training package for prison staff and peer carers to identify and support people in prison with mild cognitive impairment or dementia. Training content and format was informed by the literature on dementia training in prisons and analysis of qualitative and quantitative data from semi-structured interviews with prison staff and a survey administered to prison governors and healthcare managers, both of which explored current provision of dementia training and training needs. A stakeholder working group reviewed and revised the training during two interactive meetings. Future research to evaluate the effectiveness of the training in practice is required.

Timesweeper: accurately identifying selective sweeps using population genomic time series.

Despite decades of research, identifying selective sweeps, the genomic footprints of positive selection, remains a core problem in population genetics. Of the myriad methods that have been developed to tackle this task, few are designed to leverage the potential of genomic time-series data. This is because in most population genetic studies of natural populations, only a single period of time can be sampled. Recent advancements in sequencing technology, including improvements in extracting and sequencing ancient DNA, have made repeated samplings of a population possible, allowing for more direct analysis of recent evolutionary dynamics. Serial sampling of organisms with shorter generation times has also become more feasible due to improvements in the cost and throughput of sequencing. With these advances in mind, here we present Timesweeper, a fast and accurate convolutional neural network-based tool for identifying selective sweeps in data consisting of multiple genomic samplings of a population over time. Timesweeper analyzes population genomic time-series data by first simulating training data under a demographic model appropriate for the data of interest, training a one-dimensional convolutional neural network on said simulations, and inferring which polymorphisms in this serialized data set were the direct target of a completed or ongoing selective sweep. We show that Timesweeper is accurate under multiple simulated demographic and sampling scenarios, identifies selected variants with high resolution, and estimates selection coefficients more accurately than existing methods. In sum, we show that more accurate inferences about natural selection are possible when genomic time-series data are available; such data will continue to proliferate in coming years due to both the sequencing of ancient samples and repeated samplings of extant populations with faster generation times, as well as experimentally evolved populations where time-series data are often generated. Methodological advances such as Timesweeper thus have the potential to help resolve the controversy over the role of positive selection in the genome. We provide Timesweeper as a Python package for use by the community.

Perceived naturalness of emotional voice morphs

ABSTRACT Research into voice perception benefits from manipulation software to gain experimental control over acoustic expression of social signals such as vocal emotions. Today, parameter-specific voice morphing allows a precise control of the emotional quality expressed by single vocal parameters, such as fundamental frequency (F0) and timbre. However, potential side effects, in particular reduced naturalness, could limit ecological validity of speech stimuli. To address this for the domain of emotion perception, we collected ratings of perceived naturalness and emotionality on voice morphs expressing different emotions either through F0 or Timbre only. In two experiments, we compared two different morphing approaches, using either neutral voices or emotional averages as emotionally non-informative reference stimuli. As expected, parameter-specific voice morphing reduced perceived naturalness. However, perceived naturalness of F0 and Timbre morphs were comparable with averaged emotions as reference, potentially making this approach more suitable for future research. Crucially, there was no relationship between ratings of emotionality and naturalness, suggesting that the perception of emotion was not substantially affected by a reduction of voice naturalness. We hold that while these findings advocate parameter-specific voice morphing as a suitable tool for research on vocal emotion perception, great care should be taken in producing ecologically valid stimuli.

Routine Photography of Injuries: A Comparison Between Smartphone Cameras and Digital Single-Lens Camera-A Pilot Study.

Ten lesions were photographed with an entry-level (HUAWEI P smart 2019), a midrange (Samsung Galaxy S8) and a high range (Apple Iphone XR) smartphone camera and with a digital single-lens camera (DSLC). Images were independently rated by 3 pathologists, based on comparison to the real lesion and "visual impact." Difference of perceptual lightness coordinates between smartphones and the criterion standard (DSLC) was calculated.The highest ranking for adherence to reality was obtained with DSLC, while the highest ranking for visual impact was obtained with the Iphone. The color representation better reflecting the criterion standard (DSLC) was obtained for the entry-level smartphone.All the devices allow to assess the general features (ie, the color, the shape, and the main characteristics) of an injury during a forensic autopsy. However, results might be different when photos are obtained in suboptimal, such as low-light, conditions. Moreover, images acquired through a smartphone camera might be unsuitable for later image exploitation, such as enlargement of a portion of the image to magnification of a detail, which seemed not relevant when the photo was shot. Only a raw image, acquired using a dedicated camera and deactivating images manipulation software, might allow the preservation of the true data.

Open-source simulation of strongly-coupled fluid-structure interaction between non-conformal interfaces

Design code-based “life-safety” requirements for structural earthquake and tsunami design offer reasonable guidelines to construct buildings that will remain standing during a tsunami or seismic event. Much less consideration has been given to assessing structural resilience during sequential earthquake and tsunami multi-hazard events. Such events present a series of extreme loading scenarios, where damage sustained during the earthquake influences structural performance during the subsequent inundation. Similar difficulties exist with respect to damage sustained during tropical events, as wind and fluid loading may vary with structural response or accumulated damage. To help ensure critical structures meet a “life-safety” level of performance during such multi-hazard events, analysis software capable of simulating simultaneous structural and fluid dynamics must be developed. To address this gap in understanding of non-linear fluid-structure-interaction (FSI), an open-source tool (FOAMySees) was developed for simulation of tsunami and wave impact analysis of post-earthquake non-linear structural response of buildings. The tool is comprised of the Open-source Field Operation And Manipulation software package and OpenSeesPy, a Python 3 interpreter of OpenSees. The programs are coupled via preCICE, a coupling library for partitioned multi-physics simulation. FOAMySees has been written to work in a Linux OS environment with HPC clusters in mind. The FOAMySees program offers a partitioned conventional-serial-staggered coupling scheme, with optional implicit iteration techniques to ensure a strongly-coupled two-way FSI solution. While FOAMySees was developed specifically for tsunami-resilience analysis, it may be utilized for other FSI applications with ease. With this coupled Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) program, tsunami and earthquake simulations may be run sequentially or simultaneously, allowing for the evaluation of non-linear structural response to multi-hazard excitation.

Detection of tamper forgery image in security digital mage

Every industry that uses digital photos is concerned about image security. Forensics and public safety have long relied on suspect photos, crime scene photos, biometric photos, and other images. As digital imaging has advanced, the use of digital images iun this field has grown significantly. While digital image processing has helped to develop many new approaches in forensic research, it has also simplified image manipulation. The public availability of various snipping image manipulation software has made digital image validity a problem. It's used as strong evidence in a variety of crimes, as well as documentation for a variety of reasons. The advancement of photo processing and editing software has simplified and made it more accessible to create and modify photographs. The most common types of picture forgery are copy-move forgery and splicing images. To conceal or display an error scenario, a portion of a photograph is duplicated and pasted further in the photograph, and splicing an image means two images in one image. This research looks at different types of digital image forgeries as well as forgery detection software. A review of existing approaches for detecting faked images was conducted.

HIGH ORDER SECOND DERIVATIVE DIAGONALLY IMPLICIT MULTISTAGE INTEGRATION METHODS FOR ODES

Construction of second derivative diagonally implicit multistage integration methods (SDIMSIMs) as a subclass of second derivative general linear methods with Runge–Kutta stability property requires to generate the corresponding conditions depending of the parameters of the methods. These conditions which are a system of polynomial equations can not be produced by symbolic manipulation packages for the methods of order p ≥ 5. In this paper, we describe an approach to construct SDIMSIMs with Runge–Kutta stability property by using some variant of the Fourier series method which has been already used for the construction of high order general linear methods. Examples of explicit and implicit SDIMSIMs of order five and six are given which respectively are appropriate for both non-stiff and stiff differential systems in a sequential computing environment. Finally, the efficiency of the constructed methods is verified by providing some numerical experiments.

The detection of copy move forgery image methodologies

In every area that uses digital photos, image security is a major concern. Photos of suspects, crime scene photos, biometric photographs, and other images have long been used in forensic investigations and public safety. With the evolution of digital imaging, the digital images used in this area have increased significantly. As much as digital image processing has facilitated the development of numerous new approaches in forensic research, it has also made image manipulation simple. Digital image validity has become a problem with the public availability of various snipping image manipulation software. As a result, the need for image tampering detection software has become essential. Digital photographs have become widely used in past years for a variety of applications. The material will be disseminated through print media, the website, as well as scholarly publications. It is utilized as powerful evidence in numerous offenses as well as documentation for something like a range of functions The introduction to the photo processing and editing tools has made it simple and accessible to create or change photographs. Are of the most frequent kind of picture forgery is a copy-move forgery, in which a portion like a photographic is duplicated as well as pasted further in a photo to conceal at some point crucial or display an error scenario. This study examines many sorts of digital image forgeries as well as the detection of forgery tools. A review of available approaches for faked images was conducted.

Feature Selection for Airbone LiDAR Point Cloud Classification

The classification of airborne LiDAR data is a prerequisite for many spatial data elaborations and analysis. In the domain of power supply networks, it is of utmost importance to be able to discern at least five classes for further processing—ground, buildings, vegetation, poles, and catenaries. This process is mainly performed manually by domain experts with the use of advanced point cloud manipulation software. The goal of this paper is to find a set of features which would divide space well enough to achieve accurate automatic classification on all relevant classes within the domain, thus reducing manual labor. To tackle this problem, we propose a single multi-class approach to classify all four basic classes (excluding ground) in a power supply domain with single pass-through, using one network. The proposed solution implements random forests and gradient boosting to create a feature-based per-point classifier which achieved an accuracy and F1 score of over 99% on all tested cases, with the maximum of 99.7% for accuracy and 99.5% for F1 score. Moreover, we achieved a maximum of 81.7% F1 score for the most sparse class. The results show that the proposed set of features for the LiDAR data cloud is effective in power supply line classification.

Non-Facial Video Spatiotemporal Forensic Analysis Using Deep Learning Techniques

Digital content manipulation software is working as a boon for people to edit recorded video or audio content. To prevent the unethical use of such readily available altering tools, digital multimedia forensics is becoming increasingly important. Hence, this study aims to identify whether the video and audio of the given digital content are fake or real. For temporal video forgery detection, the convolutional 3D layers are used to build a model which can identify temporal forgeries with an average accuracy of 85% on the validation dataset. Also, the identification of audio forgery, using a ResNet-34 pre-trained model and the transfer learning approach, has been achieved. The proposed model achieves an accuracy of 99% with 0.3% validation loss on the validation part of the logical access dataset, which is better than earlier models in the range of 90-95% accuracy on the validation set.

Phased Array System Toolbox Pack Overview for New Course «5G Smart Antennas Technologies»

In the field of smart antenna technologies, approaches based on simulation modeling in special Matlab software, including the Phased Array System Toolbox extension package, deserve special attention. This package provides the implementation of algorithms and methods for modeling antenna arrays (AA) and beamforming (BF) systems in various applications, including radio communication, radar and radio navigation systems. Using the capabilities of this extension package, you can analyze the performance of active and passive AAs of various geometric configurations, including complex AAs formed from composite arrays of elements. The simulation models built with this expansion package allow the formation and processing of signals using models and methods of beamforming, when working on transmission and reception. For LTE and 5G NR mobile networks, satellite systems and WLANs, the PAST extension package allows modeling multipath AAs, including those operating in the adaptive BF mode. The extension package includes models of digital and hybrid BF algorithms that operate as part of massive MIMO spatial signal processing systems in the mmWave. Simulation capabilities in the extension package include, but are not limited to, reproducing fading conditions in a multipath radio channel and evaluating their impact on communication systems with an AP; algorithms and methods for determining signal direction of arrival (DOA). In this paper, we review the coordinate systems used in the PAST extension package. Subject of study. The article is devoted to an overview of the PAST extension package for use in the new 5G Smart Antenna Technologies training course. Method. The study of the possibilities of the PAST extension package is carried out by the simulation. Main results. The result of this work is an overview of the coordinate systems in basic software tools of the PAST extension package for use in the new course "5G Smart Antenna Technologies". Practical significance. This review introduces the capabilities of the PAST extension package and is the foundation of methodological support in the implementation of algorithms and methods for modeling antenna arrays and beamforming systems within the framework of the new training course “5G Smart Antenna Technologies”.