Built-in Functions Research Articles

Mapping of digital pedagogies in higher education

The purpose of this research is to analyse the evolution and trends of research into digital pedagogy in higher education through the application of bibliometric analysis and systematic review of scientific output. For the bibliometric analysis, the built-in functions of WoS were used, including Analyze results and Citation report. The VOSviewer software was employed to construct bibliometric maps. The analysis focuses on studies about digitalisation, university education and education quality, three categories that are grouped around digital pedagogies and methodologies. The sample contains 242 scientific publications, including articles (65.7%), publications published in the United States (17.7%) and publications financed by the European Commission (3.71%). Barber, W., and Lewin, C., are the authors with the greatest impact. The scientific output forms three networks: the “social network” (2000–2010), the “digitalisation network” (2011–2015) and the “network of the expansion of digital pedagogy” (2016–2023). The most-mature research (2005–2009) concerns the integration of technologies in education. The research with the greatest impact (2020–2022) looks at digital pedagogy and its implementation during the situation created by COVID-19. This research shows that digital pedagogy has come a long way over the last twenty years, but it is at the same time a topical area today. The paper opens up future paths for research such as the development of more-flexible pedagogies that can be adapted to different pedagogical scenarios.

Hall Current and Thermal Radiation Effects on MHD Casson Nanofluid Flow Past in The Presence of Heat Source/Sink, Brownian Motion and Thermophoresis

The effect of Hall current and thermal radiation on the MHD flow of an electrically conducting Casson nanofluid across a constantly extending surface in the presence of Heat source/sink, Brownian motion and Thermophoresis has been analyzed and investigated. Vertical application of a transverse magnetic field, with the premise that the Reynolds number is relatively low. The appropriate similarity transformations are used to convert the controlling partial differential equations into non-linear ordinary differential equations. The shooting technique generates numerical solutions for the dimensionless velocity, temperature, and nanoparticle concentration. These three variables are all taken into consideration. The findings are bolstered further by the outcomes acquired via MATLAB's built-in functions. Using graphs, the discussion will focus on the effects that the hall current parameter, thermal radiation parameter, Brownian motion parameter, thermophoresis parameter, and magnetic parameter have on the velocities, concentrations, and temperatures. To get insight into the internal behavior of the emerging parameters, a numerical calculation of the skin friction coefficient along the x and z axes, the local Nusselt number, and the Sherwood number are all performed.

Thermodynamical study of chemically-reactive and thermal-radiative magnetized oscillatory Couette flow in a porous medium filled channel

The thermodynamical study of a mathematical model of unsteady natural convective MHD oscillatory flow through a porous medium-filled channel of infinite plates with chemical reaction and thermal radiation effect is taken into account in this respective research. The time-dependent flow governing equations (PDEs); comprises momentum, energy and concentration equations are derived for the concerned physical model and converted into dimensionless second-order ordinary differential equations (ODEs) for fluctuation of small amplitude. Further, the set of ODEs is solved by MATLAB's built-in dsolve function. The graphical analysis of fluid velocity, temperature and concentration profiles has been explicated for flow parameters. According to the results, the transient velocity and concentration profiles expand when the chemical reaction parameter and Schmidt number increase, whereas a strong magnetic field retards the transient velocity profile. In addition, the velocity, temperature, and concentration profiles decline whenever the frequency of oscillation is increased. The elucidated flow model and mathematical results are significant to be used in real-life applications, including packed bed reactors, chemical reactors, cooling the towers and rocket engines, designing of heat exchangers, sewage and wastewater treatment, chemical and magnetic filtration, and separation etc.

The influence of the isolation of queen bee on its reproductive capacity and honey productivity of bees

The technological method of isolation of queen bees lies in more reasonable ways of using the potential of working bees, increasing their life expectancy, obtaining strong flying bees and also increasing the honey collection. The study of optimal terms of isolation of queen bees, their reproductive activity, characteristics of biological connections between physiological state of bees and collecting carbohydrate food in varying natural and climatic conditions is of particular practical and scientific interest. In the presented work the data of experimental studies on influence of isolation of queen bees on their reproductive capacity and honey productivity of the bee colony was provided. The goal was to study the reproductive function of isolated queen bees by accounting the brood through the beekeeping season. Methods of research. Zootechnical (selection of groups of analogues, growth accounting, the strength of the bee colony), analytical (analysis of literature data and results of research) and statistical (biometric processing of experimental data). Biometric data processing was performed on a PC using MS Excel software with the use of built-in statistical functions. Results. After the isolation, the queen bees of the research groups were characterized by low egg-laying capacity and started to lay eggs immediately after their release from isolation cage. From the end of June till the end of July the queen bees of all groups gradually increased egg-laying and by the end of accounting reduced their reproductive activity. This behavior of queen bees is primarily connected with the period of season. Therefore, the studies found that isolation has not affected the physiological changes in the reproductive system of queen bees and subsequently the strength of the bee colonies. Conclusions. On the terms of research it has been proven that technological method of isolation of queen bees during the period of honey collection up to 20 days can be successfully applied. Moreover, the use of such technological method as isolation of queen bees during the period of honey collection makes it possible to increase the productivity of queen bees. Key words: bee colony, Ukrainian steppe breed, isolation, brood, reproductive function, honey productivity.

On Beta Exponentiated Lomax-Exponential Distribution with applications

This study introduces a new Beta Exponentiated Lomax-Exponential Distribution (BELED) with special reference to its quantile function to enhance closed form solution of its parameters and make its proprietorial effect on data modeling quantifiable with exactness. The obtained BELED which accommodates heavy and light data, either skewed or not, addressed the challenges of intractable parameter estimation in previous related distributions from same family. The BELED properties which includes rth moments, characteristics function, Renyi and Shanon entropy, reliability measures as well as stress-strength model were derived. The estimator (β^) of the exponentiated parameter (β) from an in-built function was obtained in closed form at the modal point in the absence and presence of censoring. Pivot-quantile regression was used to determine the estimate of the scale (σ^) and shape α^ parameters, while the remaining beta generator induced shape parameters (a,b) were derived using maximization techniques via the constrain β^. The quantile function of BELED which averaged out the additive and multiplicative variation in a univariate data set, can be used in modeling the behavioural pattern of both discrete and continuous data.

Magnetohydrodynamic squeezing micropolar nanofluid flow confined in parallel disks with implication of Maxwell-Cattaneo law

Time-dependent electrically conducting squeezing flow of micropolar nanofluid is analyzed between two parallel disks. The bottom porous disk is fixed while the upper disk moved orthogonally along axial direction. Nanofluid features such as thermophoresis and the Brownian motion are considered using the Buongiorno theory of nanoparticles. Cattaneo-Christov model (CCM) is executed in the expression of energy equation. Uniform suction/injection is considered at bottom disk. Inclined magnetic field is accounted at an acute angle along axial direction. The constitutive model is normalized by utilizing the similarity functions. The numerical solution of flow model is developed by MATLAB built-in bvp4c function. The physical parameters are explored through graphical depiction, two-dimensional contours, three-dimensional flow phenomenon and streamlines. Since, the micropolar parameters tend to move the fluid particles in opposite way. Therefore, micro-rotational field has an increasing tendency in the left half region and decreasing behavior in the right half plane of the central region. It is obtained that the temperature field is boost up against increased squeezing Reynolds number, parameter of thermal relaxation stress and Prandtl number. Brownian movement and thermophoretic factors have a reverse phenomenon on concentration curves.

Stealthy and Flexible Trojan in Deep Learning Framework

Deep neural networks are increasingly used as the critical component of applications, bringing high computational costs. Many practitioners host their models on third-party platforms. This practice exposes DNNs to risks: A third party hosting the model may use a malicious deep learning framework to implement a backdoor attack. Our goal is to develop the realistic potential for backdoor attacks in third-party hosting platforms. We introduce a threatening and realistically implementable backdoor attack that is highly stealthy and flexible. We inject trojans by hijacking the built-in functions of the deep learning framework. Unlike existing backdoor attacks, the proposed sequential trigger is a specific sequence of clean image sets. Moreover, our attack is model agnostic and does not require retraining the model or modifying the parameters. Its stealthy is that injecting trojans will not change the models prediction for a clean image. Its flexibility lies in that adversary can remodify the trojan behavior at any time. Extensive experiments on multiple benchmarks with different frameworks demonstrate that our attack achieves a perfect success rate. And we can inject multiple trojans which do not affect each other at the same time. Analysis and experiments further show that state-of-the-art defenses are ineffective against our attacks.

EDL Aspects in swirling ionic tribological fluid flow in a squeezed/split channel underlie a high-power magnetic field

Studying electrokinetic swirling flows of ionic tribological fluid in a squeezing/splitting scenario has drawn a lot of interest due to its extensive dispensations in mechanical and manufacturing engineering. The present modelling and simulation-based study deals with an in-depth physical exploration of electric double layer (EDL) aspects in a swirling flow via a squeezing/splitting perforated channel filled with ionic tribological fluid when subjected to a high-power magnetic field with Hall current. The rudimentary momentum equations are presented by assigning partial differential equations (PDEs), which are then transmuted into non-linear ordinary differential equations (ODEs) using a compatible similarity substitution. The reduced system of coupled non-linear ODEs with proposed boundary data is dealt with numerically by dint of Runge-Kutta-Fehlberg (RKF45) formula-based shooting scheme, namely Mathematica in-built routine function bvp4c. By plotting distinctive graphs and tables, the physical impacts of emerging model parameters upon the moment profiles and engineering entities of interest are explored and interpreted. Simulated outcomes unravel with an intensification in electroosmosis and rotation parameters, the fluid pressure is discerned to rise near the channel plates while a contrary affinity prevails in the central passage. The shear impedance can be minified by adjusting the squeezing velocity. The imprinted flowlines plots unfold that the reverse flow is noticeable with the negative suction parameter. Our squeezing flow model might apply to tunnelling, semiconductors, sensing and control systems, spacecraft designing, etc.

The association between dietary inflammatory index with endometriosis: NHANES 2001-2006.

Endometriosis is a common chronic inflammatory and estrogen-dependent disease that mostly affects people of childbearing age. The dietary inflammatory index (DII) is a novel instrument for assessing the overall inflammatory potential of diet. However, no studies have shown the relationship between DII and endometriosis to date. This study aimed to elucidate the relationship between DII and endometriosis. Data were acquired from the National Health and Nutrition Examination Survey (NHANES) 2001-2006. DII was calculated using an inbuilt function in the R package. Relevant patient information was obtained through a questionnaire containing their gynecological history. Based on an endometriosis questionnaire survey, those participants who answered yes were considered cases (with endometriosis), and participants who answered no were considered as controls (without endometriosis) group. Multivariate weighted logistic regression was applied to examine the correlation between DII and endometriosis. Subgroup analysis and smoothing curve between DII and endometriosis were conducted in a further investigation. Compared to the control group, patients were prone to having a higher DII (P = 0.014). Adjusted multivariate regression models showed that DII was positively correlated with the incidence of endometriosis (P < 0.05). Analysis of subgroups revealed no significant heterogeneity. In middle-aged and older women (age ≥ 35 years), the smoothing curve fitting analysis results demonstrated a non-linear relationship between DII and the prevalence of endometriosis. Therefore, using DII as an indicator of dietary-related inflammation may help to provide new insight into the role of diet in the prevention and management of endometriosis.

Physiological and Biochemical Changes in Soybean Plants Caused by Iodine-Selenium Chelates and Phytopathogenic Bacteria

The search for effective and environmentally sound measures to fight against plant diseases caused by phytopathogenic microorganisms is of great importance. It is especially important to investigate alternative measures to protect cultivated plants that combine elements beneficial to human health such as iodine and selenium. Purpose. The study of physiological and biochemical changes in soybean leaves after artificial inoculation of plants with different strains of phytopathogenic bacteria on the background of pre-sowing treatment of seeds with a solution of iodine-selenium (I-Se) chelates. Methods. Soybean plants of the Artemis variety were grown in field conditions. Before sowing, the seeds were treated with a 1% I-Se chelated solution (I — 80 mg/L and Se citrate — 0.05 mg/L). The experimental plants were inoculated with phytopathogenic bacteria from the microbiological collection of the Zabolotny Institute of Microbiology and Virology of the National Academy of Sciences, namely Pseudomonas savastanoi pv. glycinea IMВ B-9190, P. agglomerans IMВ B-9185, and P. syringae pv. syringae IMВ B-8531. The contents of chlorophyll-a, b and carotenoids in the leaves were determined by extraction in DMSO followed by spectrophotometry. Catalase activity was determined by the method of titrimetric permanganatometry with a 0.01M solution of KMnO4, the activity to non-specific peroxidases — according to Boyarkin’s method. Evaluation of the photochemical activity of photosynthesis according to the parameters F0, Fv/Fm, and RFd was carried out by the method of induction of chlorophyll fluorescence using a portable device «Floratest». Statistical processing of experimental data was carried out using the built-in functions of the Microsoft Excel program. Results. The increase of peroxidase activity of leaves was revealed after both pre-sowing treatment with 1% I-Se solution of intact plants and inoculation of them with different strains of bacterial pathogens in the following order: I-Se &gt; I-Se+P. syringae pv. syringae 8531 &gt; I-Se+P. agglomerans 9185 &gt; I-Se+P. savastanoi pv. glycinea 9190. The catalase activity of leaves tissues increased only when infected with a specific pathogen P. savastanoi pv. glycinea 9190 (by 20.6%). After artificial inoculation with strains of both specific and facultative bacterial pathogens and the pre-sowing treatment with I-Se, there was observed an increase in the quantum efficiency of PSII (Fv /Fm) and fluorescence in decline index (Rfd). An increase in the content of chlorophyll-a (by 18%), b and carotenoids (by 7%) in the leaves after the pre-sowing treatment with I-Se has been shown. The content of chlorophyll-a in soybean leaves due to pre-sowing treatment with I-Se had the most significant increase after inoculation of P. agglomerans 9185 (20%). Due to the inoculation with a specific pathogen P. savastanoi pv. glycinea 9190 (after the pre-sowing treatment with I-Se), the content of chlorophyll-a tended to decrease, and the content of chlorophyll-b decreased by 7%. The carotenoid content in leaves increased significantly at inoculation of plant with facultative pathogens: P. agglomerans 9185 (by 28.2%) and P. savastanoi pv. syringae 8531 (by 20.7%). The chlorophyll a/b ratio increased in all experimental variants. Conclusions. 1. It was found that pre-sowing seed treatment with 1% I-Se chelated solution results in increasing disease resistance in nonspecific adult soybean plants, including increasing their thermotolerance. This is evidenced by increasing the peroxidase activity of leaves and the content of photosynthetic pigments in natural conditions: chlorophyll-a and carotenoids. 2. Inoculation of soybean plants with a specific pathogen causes an increase in catalase and peroxidase activities in leaves. The significant increase in peroxidase activity after plant inoculation with facultative pathogens was shown. 3. A significant increase in the content of chlorophyll-a in soybean leaves after inoculation with P. agglomerans 9185 and pre-sowing treatment with I-Se was observed. The significant reduction of chlorophyll-b in leaves due to the inoculation of plants with P. savastanoi pv. glycinea 9190 and pre-sowing treatment of the seeds with I-Se was shown. The most significant increase in the content of carotenoids in leaves was detected after inoculation of plants with facultative pathogens — P. agglomerans 9185 and P. syringae pv. syringae 8531. 4. Significant stimulation of both maximum quantum yield of PSII photochemistry (Fv /Fm) and the rate of carbon assimilation (Rfd) due to the pre-sowing seed treatment with I-Se and inoculation of plants with different strains of phytopathogens was observed. It resulted from the activation of antioxidant systems and increased need for assimilates due to changes in plant metabolism.

Thermal stratification effect on gravity driven transport of hybrid CNTs down a stretched surface through porous medium

The purpose of the current article is to explore the impact of thermal stratification and medium porosity on gravity-coerced transport of hybrid carbon nanotubes down an upright extending sheet inspired by a constant applied magnetic field along with heat transfer investigation in existence of thermal radiation, viscous dispersal, and joule heating effect. Rectangular coordinates are chosen for the mathematical interpretation of the governing flow problem. Homothetic analysis is employed for the sake of simplification process. The reduced system of coupled nonlinear differential equations is dealt numerically by dint of computational software MATLAB inbuilt routine function Bvp4c. The numerical investigation is carried out for the distinct scenarios namely, (i) Presence of favorable buoyancy force, (ii) Case of purely forced convection and (iii) Presence of opposing buoyancy force. Significant Findings: The key findings include that the presence of hybrid carbon nanotubes and medium porosity contributes significantly to upsurging surface shear stress magnitude whereas, external magnetic field and velocity slip effects in an altered manner. The present study may be a benchmark in study of fueling process in space vehicles and space technology.

The Revived Interest in Ageusia Research during the COVID-19 Pandemic: A Bibliometric Analysis.

The evolution of ageusia research literature has yet to be investigated. This bibliometric study analyzed the entire ageusia research literature indexed in Web of Science, to reveal its growth and the most productive entities in terms of authors, institutions, countries, journals, and journal categories. In addition, this study aimed to identify medical conditions (and their treatments) that were frequently associated with ageusia. On 7 March 2022, the Web of Science Core Collection database was accessed with the following search query: TS = (ageusia OR "taste loss" OR "loss of taste" OR "loss of gustat*" OR "gustatory loss"). The search identified publications mentioning these terms in their title, abstract, or keywords. No additional filters were placed on publication year, language, etc. The basic publication and citation counts were extracted from the in-built functions of the database. The complete record of the publications was exported into VOSviewer, a bibliometric software for visualizations. The search yielded 1170 publications. The cumulative publication and citation counts of the ageusia research sharply increased in 2020. The most productive author was Professor Thomas Hummel from Technische Universität Dresden. Ageusia research had heavy contributions from the United States, Italy, the United Kingdom, Germany, and India. The top 5 most productive journals mainly belonged to the otorhinolaryngology and medicine categories. The medical conditions frequently investigated in ageusia research included COVID-19, cancers (head and neck, and advanced basal cell), Guillain-Barré syndrome, neurodegenerative diseases, diabetes, and Sjogren's syndrome. This study could act as a begvinner's guide for (1) clinicians who are not familiar with ageusia so that they might better understand which scenarios they need to be more aware of since ageusia could be a co-morbidity of a patient's underlying disease, and (2) for those who wish to search for relevant authors and journals for suitable publications related to the topic.

Interaction of variable diffusion coefficients with electrokinetically regulated peristalsis of Carreau-Yasuda nanofluid

In this analysis, the interaction of variable diffusion coefficients with electrokinetically modulated peristaltic motion of a radiative Carreau-Yasuda (CY) nanofluid is communicated. Here, ethylene glycol is used as the base fluid, and graphene nanoplatelets are considered nanoparticles. Unlike many existing studies, the thermophoretic diffusion term appearing in the equation of temperature and concentration is considered a variable term instead of manipulating their average values to obtain a more precise estimation of the conduct of the nanofluid. The Carreau-Yasuda (CY) model is considered to represent the non-Newtonian features of nanofluids. A mathematical model is developed under the effects of Joule heating, variable thermal conductivity, mixed convection, thermal radiation, electric field, Brownian motion, viscous dissipation, magnetic field, and thermophoresis assumptions. The entropy equation involving a variable diffusion coefficient and thermal conductivity is constructed using the second law of thermodynamics. The acquired dimensionless equations are numerically resolved with the help of built-in function. The graphical results indicate that due to Joule heating characteristics, the temperature profile increases. Manipulation of radiation and thermal conductivity parameters can improve the thermal efficiency and productivity of the system. An electroosmotic parameter causes an augmentation in the Bejan number. The nanofluid flow decreases at a higher electroosmotic velocity. The nanofluid chosen makes it possible to envisage industrial applications, for example in the field of heat extraction, without compromising mechanical performance.

Partial differential equations modeling of bio-convective sutterby nanofluid flow through paraboloid surface

In this research article, the behavior of 2D non-Newtonian Sutterby nanofluid flow over the parabolic surface is discussed. In boundary region of surface buoyancy-driven flow occurred due to considerable temperature differences produced by the reaction happen between Sutterby nanofluid and catalyst at the surface. Free convection which is sighted easily on the parabolic surface is initiated by reaction on the catalyst surface modeled the 1st order activation energy. Applications of parabolic surfaces are upper cover of bullet, car bonnet, and air crafts. Under discussion flow is modelled mathematically by implementing law of conservation of microorganism’s concentration, momentum, mass and heat. The governing equations of the system is of the form of non-linear PDE’s. By the use of similarity transform, the governing PDE`s transformed as non-dimensional ODE’s. The resultant system of non-dimensional ODE’s are numerically solved by built-in function MATLAB package named as ‘bvp4c’. Graphical representation shows the influence of different parameters in the concentration, velocity, microorganisms and temperature profiles of the system. In temperature profile, we examined the impact of thermophoresis coefficient Nt (0.1, 0.5, 1.0), Prandtl number Pr (2.0, 3.0, 4.0), and Brownian motion variable Nb (0.1, 0.3, 0.5). Velocity profile depends on the non-dimensional parameters i.e. (Deborah number De & Hartmann number Ha) and found that these numbers (De, Ha) cause downfall in profile. Furthermore, mass transfer, skin friction, and heat transfer rates are numerically computed. The purpose of the study is to enumerate the significance of parabolic surfaces for the transport of heat and mass through the flow of bio-convective Sutterby nanofluid.

Mathematical Modelling of COVID-19 Transmission Dynamics with Vaccination: A Case Study in Ethiopia

Mathematical modelling is important for better understanding of disease dynamics and developing strategies to manage rapidly spreading infectious diseases. In this work, we consider a mathematical model of COVID-19 transmission with double-dose vaccination strategy to control the disease. For the analytical analysis purpose, we divided the model into two parts: model with vaccination and without vaccination. Analytical and numerical approach is employed to investigate the results. In the analytical study of the model, we have shown the local and global stability of disease-free equilibrium, existence of the endemic equilibrium and its local stability, positivity of the solution, invariant region of the solution, transcritical bifurcation of equilibrium, and sensitivity analysis of the model is conducted. From these analyses, for the full model (model with vaccination), we found that the disease-free equilibrium is globally asymptotically stable for R v &lt; 1 and is unstable for R v &gt; 1 . A locally stable endemic equilibrium exists for R v &gt; 1 , which shows the persistence of the disease if the reproduction parameter is greater than unity. The model is fitted to cumulative daily infected cases and vaccinated individuals data of Ethiopia from May 1, 2021 to January 31 , 2022 . The unknown parameters are estimated using the least square method with the MATLAB built-in function “lsqcurvefit.” The basic reproduction number R 0 and controlled reproduction number R v are calculated to be R 0 = 1.17 and R v = 1.15 , respectively. Finally, we performed different simulations using MATLAB. From the simulation results, we found that it is important to reduce the transmission rate and infectivity factor of asymptomatic cases and increase the vaccination coverage and quarantine rate to control the disease transmission.

SlicerCBM: automatic framework for biomechanical analysis of the brain

PurposeBrain shift that occurs during neurosurgery disturbs the brain’s anatomy. Prediction of the brain shift is essential for accurate localisation of the surgical target. Biomechanical models have been envisaged as a possible tool for such predictions. In this study, we created a framework to automate the workflow for predicting intra-operative brain deformations.MethodsWe created our framework by uniquely combining our meshless total Lagrangian explicit dynamics (MTLED) algorithm for computing soft tissue deformations, open-source software libraries and built-in functions within 3D Slicer, an open-source software package widely used for medical research. Our framework generates the biomechanical brain model from the pre-operative MRI, computes brain deformation using MTLED and outputs results in the form of predicted warped intra-operative MRI.ResultsOur framework is used to solve three different neurosurgical brain shift scenarios: craniotomy, tumour resection and electrode placement. We evaluated our framework using nine patients. The average time to construct a patient-specific brain biomechanical model was 3 min, and that to compute deformations ranged from 13 to 23 min. We performed a qualitative evaluation by comparing our predicted intra-operative MRI with the actual intra-operative MRI. For quantitative evaluation, we computed Hausdorff distances between predicted and actual intra-operative ventricle surfaces. For patients with craniotomy and tumour resection, approximately 95% of the nodes on the ventricle surfaces are within two times the original in-plane resolution of the actual surface determined from the intra-operative MRI.ConclusionOur framework provides a broader application of existing solution methods not only in research but also in clinics. We successfully demonstrated the application of our framework by predicting intra-operative deformations in nine patients undergoing neurosurgical procedures.

Design of Dual-Configuration Dual-Mode Stimulator in Low-Voltage CMOS Process for Neuro-Modulation.

A dual-configuration dual-mode stimulator for neuro-modulation is proposed and designed. All the electrical stimulation patterns that frequently used for neuro-modulation can be generated by the proposed stimulator chip. Dual-configuration represents the bipolar or monopolar structure, meanwhile dual-mode stands for the current or voltage output. No matter what stimulation circumstance is chosen, biphasic or monophasic waveforms can be fully supported by the proposed stimulator chip. The stimulator chip with 4 stimulation channels has been fabricated in 0.18-μm 1.8-V/3.3-V low-voltage CMOS process with common grounded p-type substrate, which is suitable for SoC integration. The design has conquered the overstress and reliability issues in the low-voltage transistors under the negative voltage power domain. Each channel in the stimulator chip only occupies the silicon area of 0.052 mm2, and the maximum output level of stimulus amplitude is up to ±3.6 mA and ±3.6 V. With the built-in discharge function, bio-safety concern of unbalanced charge in neuro-stimulation can be dealt with properly. Moreover, the proposed stimulator chip has been applied on both imitation measurement and in-vivo animal test successfully.

The method of the real-time human detection and tracking

Today, data collected from video surveillance systems require processing. Video content analysis (VCA) or video analytics (VA) has found applications in security systems, retail, the automotive industry, smart home technologies, etc. The tasks of video analytics include the detection and tracking of objects. Usually, video analytics systems are specialized software for analyzing video data collected from webcams and intelligently assessing the situation. There are also separate video surveillance cameras with built-in video analytics functions. Software approaches to human detection and tracking are quite diverse, special applications and web applications or separate software modules are created. This work presents an approach to solving these problems using convolutional neural networks. The aim of the study is to increase the efficiency of human detection and tracking in video sequences. For this purpose, an overview of existing methods of detecting objects in images was conducted, in particular: the Viola-Jones algorithm, the histogram of oriented gradients. The choice of convolutional neural networks for solving the subtask of object detection is substantiated. The working principles, advantages and disadvantages of Faster R-CNN, YOLO, SSD and RetinaNet networks are considered. Their comparative analysis was carried out according to the indicators of speed and accuracy of recognition on the HABBOF dataset. A hybrid neural network for human detection and tracking has been developed: a convolutional neural network of the YOLO type has been improved. The created network achieved an accuracy of 39.2% at 43 frames per second. Experiments were carried out with the created network in order to evaluate the operation of the network in various conditions. It has been established that it works well in poor lighting conditions, but the issue of detecting small objects remains open.

How to implement signed-rank wilcox.test() type procedures when a center of symmetry is unknown

The aim is twofold: (1) to indicate that the one-sample Wilcoxon signed rank test cannot be used directly when a center of symmetry is unknown; and (2) to propose and examine correct schemes for applying the Wilcoxon signed rank test with an estimated center of symmetry. It turns out that the Wilcoxon signed rank test and the sign test for symmetry do not provide valued outputs, when unknown centers of symmetry are estimated using underlying data. In such scenarios, these tests are not null-distribution-free and break down completely even based on samples with large numbers of observations. Theoretical propositions are shown to propose a simple correction of the corresponding R built-in function, employing p-value-based procedures. To perform the proposed algorithms, we develop new customized procedures for estimating the integrated squares of densities, probability weighted moments and special values of density functions. It is shown that the proposed testing strategies have Type I error rates under good control as well as exhibit high and stable power characteristics.The proposed algorithms can be applied for modifying Wilcoxon tests type procedures in different statistical software.

Development and Performance Evaluation of Photovoltaic (PV) Evaluation and Fault Detection System Using Hardware-in-the-Loop Simulation for PV Applications

This paper originally presents a photovoltaic (PV) evaluation and fault detection (PVEFD) system for PV applications based on the Internet of Things (IoT) technology. The PVEFD system consists of an STM32F103C8T6 chip with a 32-bit Arm Cortex-M3 reduced instruction set computer (RISC) and 12-bit resolution analog-to-digital converter (ADC) to measure important parameters of PV applications, such as solar irradiance as well as the back-surface cell temperature, operating voltage, and output current of PV devices. The measured data of irradiance as well as back-surface cell temperature and operating voltage of PV devices are then fed into a built-in PV model in the on-chip Arm Cortex-M3 RISC for hardware-in-the-loop (HIL) simulation to obtain the simulated output current and power of PV devices. The resulting data are transmitted to a cloud server for remote monitoring and automatic warning function through a Raspberry PI 3 module and WiFi network. The simulation results are compared with in-field measurement data from PV modules and displayed on a human-machine interface (HMI) and an Android app. The results of the study illustrated that the proposed system features high accuracy and sufficient confidence. Furthermore, the fault detection function through the built-in HIL simulation function in PV systems was validated. Therefore, the proposed system is a small, compact, and cost-effective HIL-on-chip machine for remote surveillance of PV power systems.