Search

The immense growth of the cloud infrastructure leads to the deployment of several machine learning as a service (MLaaS) in which the training and the development of machine learning models are ultimately performed in the cloud providers’ environment. However, this could also cause potential security threats and privacy risk as the deep learning algorithms need to access generated data collection, which lacks security in nature. This paper predominately focuses on developing a secure deep learning system design with the threat analysis involved within the smart farming technologies as they are acquiring more attention towards the global food supply needs with their intensifying demands. Smart farming is known to be a combination of data-driven technology and agricultural applications that helps in yielding quality food products with the enhancing crop yield. Nowadays, many use cases had been developed by executing smart farming paradigm and promote high impacts on the agricultural lands.

AbstractLet Rbe a commutative ring and Hbe a multiplicative prime subset of R. The generalized total graph is the undirected simple graph with vertex set Rand two distinct vertices xand yare adjacent if For a field F, is the only multiplicative prime subset of Fand the corresponding generalized total graph is denoted by In this paper, we investigate several graph theoretical properties of where is the complement of the generalized total graph of F. In particular, we characterize all the fields for which is unicyclic, split, chordal, claw-free, perfect and pancyclic.

The feasibility of using Corning's edge strength measurement system (ESMS) for ultra‐thin LCD panels has been demonstrated. Panels were used to validate the load‐to‐stress correlation: digital image correlation, finite element analysis and mirror radius measurement all showed good agreement, supporting the robustness of the strength measurement. The edge strength of panels was measured by both static and dynamic ESMS. Test results revealed that dynamic ESMS is advantaged over static in better capturing the relevant flaw population owing to its larger test area. Accurate edge strength measurement via ESMS coupled with selective fracture analysis on the weakest flaws will assist in improving the edge strength of ultra‐thin LCD panels

In recent years, there has been a significant demand for lightweight converters that provide exceptional control performance while generating minimal acoustic noise. This has resulted in higher switching signals for hard- switched 2-level low voltage 3-phase inverters. However, the increased switching frequencies have a negative impact on the inverters’ efficiency, requiring the use of expensive switch technology to maintain high efficiency. This paper aims to tackle these challenges by introducing the design and implementation of a extremely effective 3-Level T-Type Neutral Point Clamped (NPC) inverter designed for Electric Vehicle (EV) applications. 3-Level T-Type NPC inverter associates the strengths of both NPC and T-Type inverters. Similar towards the NPC, it offers a lower breakdown voltage for the switching devices, thereby reducing switching losses. Additionally, it shares the characteristics of the T-Type inverter, resulting in fewer conduction losses. To validate the feasibility of the converter, simulation is performed using MATLAB software, followed by the development and testing of a lab-scale prototype. The proposed three-level T-type NPC inverter have several merits over traditional 2-level inverters, including reduced distortion, switching losses, and improved efficiency. These benefits contribute to enhanced motor drive performance, reduced electromagnetic interference (EMI), and extended battery life in EVs.

There are two distinct categories of sources for generating electrical power: conventional and non-conventional. At now, traditional sources such as coal, gas, and nuclear power are widely employed for the purpose of electricity generation; nevertheless, they are associated with detrimental environmental consequences. Therefore, it is crucial to utilize renewable energy sources like sun and wind to provide some of the necessary electrical power. The driving force behind this transition is the imperative for clean energy, the mitigation of greenhouse gas emissions, and the capacity to create electricity in geographically isolated regions. A proposed solution for using solar energy in single-phase AC applications involves the implementation of an H5 converter topology. The proposed architecture employs twin input DC-DC boost converters, which incorporate solar panels and batteries, to manage the desired output DC voltage. The H5 topology has notable suitability for single-phase transformerless inverters in AC applications encompassing low and high-power demands, owing to its capacity to effectively mitigate leakage current. In order to evaluate the viability of the suggested methodology, a MATLAB simulation is performed to simulate the complete procedure. Furthermore, the development of a prototype is underway in order to assess and verify the performance and outcomes of the converter. The simulation will be conducted with either the MATLAB.

Presently, there are many more commercial applications for thermoelectric Peltier coolers, notably portable air/water refrigerators, electronics cooling processes, thermal management systems in medical applications, and others. Thus, the goal of this project is to develop an experimentally-based optimisation procedure for powered by sunlight peltier-based air conditioners and heaters for use in hospitals that are capable of running continuously. This enables patients to cook meals in the heating element and keep drugs in the cold compartment inside the cooler, both functions being incorporated into one model while also reducing the device’s dimensions and requirement for space. In this study, a model that employs perturb and observe (P&O) approaches applied to solar systems under constant and partially shady circumstances was powered by the Maximum Power Point Tracking (MPPT) methodology. Additionally, the Internet of Things modules offer user and autonomous management, while the entire system is tracked and shown on an OLED. An appropriate number of modules also reduces the expense per cooling unit for Peltier coolers and warmers.

Modeling hydrogeologic processes facilitates in accurate prediction/forecasting of groundwater level variations. Still, the uncertainty in model prediction is a major concern that requires detailed investigation. There could be several factors which introduce uncertainty such as inherent assumption, various levels of model complexity and simplicity. In general, model inputs, parameters and structure are the major sources of uncertainty while quantifying model prediction uncertainty. In this study, a genetic programming (GP) based models have been employed for forecasting groundwater level variation along with prediction uncertainty quantification. Though various sources induce uncertainty in the model prediction, the input uncertainty quantification has received little attention. Hence, the input uncertainty has been considered for the analysis in this study. The proposed method is demonstrated using measured monthly values of rainfall and corresponding groundwater level data of Amarawathi basin, India. It is observed that the prediction along with uncertainty quantification improves the confidence level of models while making decisions, in particular for effective planning and management of groundwater resources.

Wound is a disruption of normal anatomic structure and function of the skin, and any infection in this constitutes wound infection. Wound infection delays wound healing, and it causes wound breakdown, leading to increased hospital stay, morbidity and mortality. Most of the published data available focus on surgical site infections. In the developing countries, however, wound infection is an important cause of hospital mortality and morbidity. No data are available on the microbial profile of the wounds presenting at our hospital.

In this work, we developed a perovskite structured samarium cobalt oxide nanoparticles (SmCoO3NPs) with the aid of the co-precipitation method. The rare earth metal (Sm) and cobalt oxide combined to form a perovskite lattice structure. One-pot route synthesized SmCoO3NPs were scrutinized successfully through various physicochemical techniques. Concerning its effective thermal stability and electrical properties, the synthesized SmCoO3NPs have been effectively implemented in the electrochemical evaluation of promethazine hydrochloride (PHY) using cyclic voltammetry. The electrochemical detection of PHY was performed through SmCoO3NPs-modified glassy carbon electrode (GCE) and unmodified GCE. The electron transfer kinetics, effect of scan rate, the influence of pH, electroactive surface area, selectivity, and sensitivity have been studied. The electron charge transfer rate (Rct) and electrolyte resistance (Rs) were calculated to be 105.59 (Ω) and 150 (Ω) in the ferricyanide probe, indicating great facilitation of the electron transfer between PHY and SmCoO3NPs deposited on the electrode surface. Further, the optimized SmCoO3-modified GCE exemplifies excellent selectivity, storage stability, reproducibility, repeatability, detection limit (5 nM), sensitivity (0.594 μA μM−1 cm−2), and wide consecutive linear ranges, respectively. Besides, the proposed method has been effectively employed for the detection of PHY in the various real samples which reveals good recoveries of 95.40–99.17%.

Herein, we reported the fabrication of porous iron oxide/carbon black (P–Fe2O3/CB) composite through a two-step engineering method. At first, Prussian blue microcubes were used as a precursor and further calcined to form P–Fe2O3microcubes. The intercalation of CB nanoparticles with P–Fe2O3nanocubes was processed through the ultrasonication method. The obtained P–Fe2O3/CB were successfully scrutinized through various physiochemical characterization methods. The proposed P–Fe2O3/CB-modified glassy carbon electrode sensor was successfully implemented in the electrochemical sensing of chlorpromazine hydrochloride due to its very low charge transfer resistance (Rct) compared to the other electrode modifiers. The sensitive detection of CPMH through differential pulse voltammetry exemplifies an excellent electroanalytical performance such as a wide linear range of 0.5–1472 μM, a lower detection limit (0.001 μM), and an appraisable sensitivity of 1.99 μA/μM cm−2due to its availability of a high number of active sites and its large surface area, respectively. It also expresses excellent selectivity, repeatability, reproducibility, and stability results. Moreover, the practical feasibility of the as-fabricated P–Fe2O3/CB/glassy carbon electrode sensor shows exquisite recovery (98.1–100.8%) results with an appraisable current response in various biological, pharmaceutical, and environmental samples.

Annular centrifugal extractor is a favoured solvent extraction contactor where process flowsheet requires a low hold-up, lower residence times and compact layout. However during operation of annular centrifugal extractor, a small entrainment, generally of the order of few hundred ppm, is always observed. To characterise this small entrainment, hydrodynamic experiments in a no-mass transfer mode were conducted on a 40 mm centrifugal extractor with 30%TBP/dodecane and acidified water. The aqueous product stream was analysed by dynamic light scattering based methods and drop size distribution was experimentally measured. The maximum entrained micro-drop size was typically below 1 μm in most of the cases and in the rest it was well below 10 μm. Thus the original assertion, that small entrainment occurred due to micro-sized drops, was proved right. However due to complex relations of peak locations and relative peak intensities to the physical and operating properties of solvent extraction system, mathematical modelling or correlation of experimental results was not feasible.

The aim of the present study was to design a proniosomal drug delivery system of captopril to overcome the limitations of conventional dosage form and to optimize encapsulation parameters to achieve a delivery system suitable for in vitro investigations. Proniosomes are dry powders, which makes richer processing and packing possible. A surfactant coated carrier method was utilized to formulate proniosomal powder containing captopril as a model drug. This system was evaluated in vitro for drug loading, vesicle size, angle of repose, encapsulation efficiency, and stability studies. This method of proniosome loading resulted in 54.16−70.10% of encapsulation. This study examined critical parameters such as type and composition of surfactant. Proniosomes were investigated by transmission electron microscopy for characterization. Four week stability data for proniosomal powder is reported, and at all sampling points significantly higher drug retention was observed. Thus, it can be concluded that the encapsulation of captopril in proniosomes facilitates the controlled release and constitutes a good choice.

In this paper, the idea of ∈,∈∨q˘-bipolar fuzzy b-ideals and an ∈,∈∨q˘-bipolar fuzzy ideals of BCK/BCI-algebras is delivered, and their related properties are investigated with the aid of some examples. We also provide the connection between ∈,∈∨q˘-bipolar fuzzy ideals and bipolar fuzzy ideals and ∈,∈∨q˘-bipolar fuzzy b-ideals and bipolar fuzzy b-ideals by way of counterexamples.