Search Results (616)

Given the widespread accessibility of content creation and sharing, false information proliferation is a growing concern. Researchers typically tackle fake news detection (FND) in specific topics using binary classification. Our study addresses a more practical FND scenario, analyzing a corpus with unknown topics through multiclass classification, encompassing true, false, partially false, and other categories. Our contribution involves: (1) exploring three BERT-based models—SBERT, RoBERTa, and mBERT; (2) enhancing results via ChatGPT-generated artificial data for class balance; and (3) improving outcomes using a two-step binary classification procedure. Our focus is on the CheckThat! Lab dataset from CLEF-2022. Our experimental results demonstrate a superior performance compared to existing achievements but FND’s practical use needs improvement within the current state-of-the-art. Full article

This study describes the use of electrochemical sensors to detect and quantify several statins (rosuvastatin and simvastatin) in pharmaceutical products. Two types of commercially screen-printed sensors were used and compared: one based on carbon (SPCE) and the other modified with gold nanoparticles and multi-walled carbon nanotubes (SPE/GNP-MWCNT). Cyclic voltammetry was employed for determination. The AuNP-MWCNTs/SPCE sensor outperformed the SPCE sensor, displaying excellent electrochemical properties. It demonstrated high sensitivity with low limits of detection (LOD) and quantification (LOQ) values: 0.15 µM and 5.03 µM, respectively, for rosuvastatin and 0.30 µM and 1.01 µM, respectively, for simvastatin. The sensor had a wide linear range of 20–275 µM for rosuvastatin and 50–350 µM for simvastatin. Using the AuNP-MWCNTs/SPCE sensor, rosuvastatin and simvastatin were successfully quantified in pharmaceutical products. The results were validated towards producer-reported values (standardized drugs) and a conventional analysis method (FTIR). The sensor exhibited excellent stability, reproducibility, and analytical recovery ranging from 99.3% to 106.6% with a low relative standard deviation (RSD) of less than 1%. In conclusion, the AuNP-MWCNTs/SPCE sensor proved to be a reliable and sensitive tool for detecting and quantifying statins in pharmaceutical products. Its superior electrochemical properties, low LOD and LOQ values, wide linear range, and high analytical recovery make it a promising choice for pharmaceutical quality control. Full article

This work presents a low-cost device for evaluating Variable Orifice Flow Meters (VOFM) used in medical mechanical ventilation applications. Specifically, the equipment was used to assess the impact of length and thickness on pressure drop for different flows in a rectangular geometry VOFM. A total of six VOFMs, with three different lengths and two different thicknesses, were evaluated. All VOFMs were stimulated with an airflow ranging from 0 $\mathrm{L}.{\mathrm{m}\mathrm{i}\mathrm{n}}^{-1}$ to 90 $\mathrm{L}.{\mathrm{m}\mathrm{i}\mathrm{n}}^{-1}$, with increments of approximately 2 $\mathrm{L}.{\mathrm{m}\mathrm{i}\mathrm{n}}^{-1}$. The experiments conducted with the device showed a strong relationship between pressure drop $∆P$ and flow rate $Q$ in the evaluated VOFMs, with two different zones: one exhibiting non-linear behavior and another showing linear behavior. The results suggest that increased length and decreased thickness lead to higher sensitivity. However, it is essential to reduce the cross-sectional area to mitigate nonlinear effects of the sensor. Full article

Titanium surfaces were anodized to create nanotube structures utilizing an aqueous electrolyte made of xanthan gum (XG) and sodium fluoride. The purpose of employing this type of anodizing solution was to investigate the impact of XG addition on the morphology and organization of nanotubes. As far as we know, this is the first time that TiO₂ nanotubes, made using aqueous electrolytes with XG as an additive, have been reported. The organization of the nanotubes was measured using the regularity ratio (RR) from the fast Fourier transformation (FFT) pictures. Contrary to the nanotubes formed in aqueous solutions without XG, the addition of XG to the aqueous electrolyte improved the nanotube organization, with no effect on packability. Based on the findings of this experimental work, organized and homogeneous nanotubular structures might be produced utilizing an inexpensive and non-toxic aqueous electrolyte. Full article

The paper explores the challenges of constructing self-organizing wireless mobile ad hoc networks (MANETs) utilizing Optimal Link State Routing (OLSR) with MPR (MultiPoint Relay) optimization and quality control through the RSVP (Resource Reservation Protocol). Analytical expressions are presented for calculating the achievable network characteristics, including route acquisition time, network efficiency (routing overhead), packet transmission delay (end-to-end delay), and signal propagation losses between nodes assuming no packet collisions within the network nodes. The possibility of network scalability is analyzed depending on the scenarios of operation and the number of network nodes. Recommendations for the construction and scalability of self-organizing wireless networks are formulated based on the conducted evaluations and calculations. Full article

This research aims to employ and qualify the bio-inspired algorithms: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution Algorithm (DE) in the extraction of the parameters of the circuit equivalent to a photovoltaic module in the models of a diode and five parameters (1D5P) and two diodes and seven parameters (2D7P) in order to simulate the I-V characteristics curves for any irradiation and temperature scenarios. The peculiarity of this study stands in the exclusive use of information present in the module’s datasheet to carry out the full extraction and simulation process without depending on external sources of data or experimental data. To validate the methods, a comparison was made between the data obtained by the simulations with data from the module manufacturer in different scenarios of irradiation and temperature. The algorithm bound to the model with the highest accuracy was DE 1D5P, with a maximum relative error of 0.4% in conditions close to the reference and 3.61% for scenarios far from the reference. On the other hand, the algorithm that obtained the worst result in extracting parameters was the GA in the 2D7P model, which presented a maximum relative error of 9.59% in conditions far from the reference. Full article

Solar energy is an unlimited and sustainable energy source that holds great importance during the global shift towards environmentally friendly energy production. However, integrating solar power into electrical grids is challenging due to significant fluctuations in its generation. This research aims to develop a model for predicting solar radiation levels using a hybrid power system in the Gorno-Badakhshan Autonomous Oblast of Tajikistan. This study determined the optimal hyperparameters of a multilayer perceptron neural network to enhance the accuracy of solar radiation forecasting. These hyperparameters included the number of neurons, learning algorithm, learning rate, and activation functions. Since there are numerous combinations of hyperparameters, the neural network training process needed to be repeated multiple times. Therefore, a control algorithm of the learning process was proposed to identify stagnation or the emergence of erroneous correlations during model training. The results reveal that different seasons require different hyperparameter values, emphasizing the need for the meticulous tuning of machine learning models and the creation of multiple models for varying conditions. The absolute percentage error of the achieved mean for one-hour-ahead forecasting ranges from 0.6% to 1.7%, indicating a high accuracy compared to the current state-of-the-art practices in this field. The error for one-day-ahead forecasting is between 2.6% and 7.2%. Full article

An Internet of things (IoT) network is a distributed set of “smart” sensors, interconnected via a radio channel. The basic method of accessing the radio channels for these networks is Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA), in which access is carried out on the basis of contention, and confirmation of the correct reception of the packet is achieved using a receipt. If the sizes of information packets are small and comparable to the sizes of receipts, then the transmission of receipts requires a significant bandwidth of the channel, which reduces the efficiency of the network. This problem exists not only for IoT networks but also for monitoring systems, operational management of fast processes, telemetry, short messaging and many other applications. Therefore, an urgent task is to develop effective methods of multiple random access in the transmission of short information packets, the size of which is comparable to the size of receipts. To solve this problem, the authors proposed modifications of CSMA/CA random access in which, when packet collisions are detected, a diagnostic message (DM) is generated and transmitted in the broadcast mode. Based on simulation modeling, it is shown that in a wide range of network loads, the proposed random access options provide an increase in network capacity (the number of connected subscribers) of 1.5–2 times compared to the basic CSMA/CA access method when the size of the information packet is an order of magnitude larger than the size of receipts. The variant of access without acknowledgment is also considered, in which, as shown by the simulation results, at sufficiently large loads, the network can go into an unstable state. Full article

The main contribution of this paper is the inductive compensation of a wireless inductive power transmission circuit (IPT) with resonant open-loop inductive coupling. The variations in the coupling coefficient k due to the misalignment of the transmitter and receiver are compensated with only one auxiliary inductance in the primary of the inductive coupling. A low-power prototype was implemented with the following specifications: input voltage Vin = 27.5 V, output power Po = 10 W, switching frequency f = 500 kHz, output voltage Vo = 12 V, transmission distance d = 1.5 mm. Experimental results varying the distance “d” with several values of the compensation inductor demonstrate the feasibility of the proposal. An efficiency of 75.10% under nominal conditions was achieved. This proposal is a simple compensation topology for wireless chargers of cellular phones presenting small distances between the transmitter and receiver. Full article

This general review paper presents a condensed view of recent inventions in the Additive Manufacturing (AM) field. It outlines factors affecting the development and commercialization of inventions via research collaboration and discusses breakthroughs in materials and AM technologies and their integration with emerging technologies. The paper explores the impact of AM across various sectors, including the aerospace, automotive, healthcare, food, and construction industries, since the 1970s. It also addresses challenges and future directions, such as hybrid manufacturing and bio-printing, along with socio-economic and environmental implications. This collaborative study provides a concise understanding of the latest inventions in AM, offering valuable insights for researchers, practitioners, and decision makers in diverse industries and institutions. Full article

This paper provides preliminary research regarding the implementation and evaluation of a hybrid mechanism of authentication based on fingerprint recognition interconnected with RFID technology, using Arduino modules, that can be deployed in different scenarios, including secret classified networks. To improve security, increase efficiency, and enhance convenience in the process of authentication, we perform a comparative assessment between two homomorphic encryption algorithms, the Paillier partial homomorphic algorithm and the Brakerski–Gentry–Vaikuntanathan fully homomorphic encryption scheme, applied to biometric templates extracted from the device mentioned above, by analyzing factors such as a histogram analysis, mean squared error (MSE), peak signal-to-noise ratio (PSNR), the structural similarity index measure (SSIM), the number of pixel change rate (NPCR), the unified average changing intensity (UACI), the correlation coefficient, and average encryption time and dimension. From security and privacy perspectives, the present findings suggest that the designed mechanism represents a reliable and low-cost authentication alternative that can facilitate secure access to computer systems and networks and minimize the risk of unauthorized access. Full article

The use of embedded processors is the most promising direction in the development of automatic control systems. The article is devoted to analog models and technical solutions that allow continuous analysis of information in a technical system in order to synthesize control signals. Technical solutions are obtained on the basis of continuum logic methods, which aim to increase the speed of embedded computing networks, reduce power consumption, and unify the element base of analog processors. The effect of high speed is achieved due to the transition from sequential digital calculations to parallel synthesis of analog control signals. Examples of the implementation of schemes for the synthesis of control commands using the developed models of logical operations are given. Full article

The increasing popularity of electric vehicles presents both opportunities and challenges for the advancement of lithium battery technology. A new longitudinal-flow heat dissipation theory for cylindrical batteries is proposed in order to increase the energy density and uniform temperature performance of cylindrical lithium-ion battery packs while also shrinking their size by roughly 10%. First, a genetic algorithm is used to identify a single cell’s thermal properties. Based on this, modeling and simulation are used to examine the thermal properties of the longitudinal-flow-cooled battery pack. It is found that the best coolant flow scheme has one inlet and one outlet from the end face, taking into account the cooling effect of the battery pack and engineering viability. Lastly, thermal dummy cells (TDCs) are used to conduct a validation test of the liquid cooling strategy. Additionally, the simulation and test results demonstrate that the liquid cooling solution can restrict the battery pack’s maximum temperature rise under the static conditions of a continuous, high-current discharge at a rate of 3C to 20 °C and under the dynamic conditions of the New European Driving Cycle (NEDC) to 2 °C. In applications where the space requirements for the battery pack are quite strict, the longitudinal-flow cooling method has some advantages. Full article

Multiple-input multiple-output (MIMO) radars offer significant advantages over conventional standalone radars in terms of target detection and localization capabilities. However, to fully exploit their potential, such systems require excellent time and phase synchronization among the central unit and the radar heads. Only recently, thanks to microwave photonics (MWP) techniques, it has been possible to develop the first coherent MIMO radar demonstrators. In this paper, a simulation tool in MATLAB programming language is proposed to model coherent MIMO radars based on MWP techniques in maritime surveillance applications. Moreover, a novel approach for estimating the radar cross section of extended maritime targets is presented. The system performance in co-located and distributed MIMO configuration, as well as in single- and multi-band operations, is evaluated by means of relevant key performance indicators (KPIs). Simulations are carried out in two close-to-reality scenarios. In the first, a co-located MIMO radar is mounted on top of a patrolling vessel. In the second, a distributed MIMO radar is deployed inside a port. The proposed KPIs are analyzed in terms of both geometric and frequency diversities of the system, laying the foundations for general system optimization criteria valid in any given surveillance application. Full article

This article discusses the topical issues of managing information security vulnerabilities in the life cycle stages of processors and computer equipment. An analysis of the experience of identifying vulnerabilities in the course of the joint design of the processor, computing module and computing complex was carried out. A number of actions have been developed and presented to ensure the control of hardware vulnerabilities in the development stage. The use of the binary translation technology of the Elbrus platform is proposed to prevent the execution of malicious software. A method has been developed to eliminate vulnerabilities in computer equipment for automated systems used for various purposes by using the Lintel binary translation system component. An experiment is described, the purpose of which was to successfully exploit the Meltdown vulnerability on a computer with an Elbrus processor. The experiment showed that, due to the peculiarities of the microarchitecture of Elbrus processors, the exploitation of Meltdown-type vulnerabilities is impossible. Full article