Personal Computer Research Articles

A Plaintext-Related and Ciphertext Feedback Mechanism for Medical Image Encryption Based on a New One-Dimensional Chaotic System

Abstract In recent years, Plaintext-Related Image Encryption (PRIE) algorithms have been introduced, demonstrating a commendable level of plaintext sensitivity to resist chosen plaintext attack (CPA). However, these approaches suffer from several drawbacks, including inability to fully reconstruct the original image, limited practical value and excessive computational demands etc.. Moreover, the exponential expansion of medical data necessitates the formulation of more secure and efficient encryption algorithms. In this paper, firstly, a novel one-dimensional chaotic map, designated as 1D-SAM, which strikes an excellent balance between structural complexity and chaotic performance is proposed. The 1D-SAM achieve a larger chaotic range and an elevated Lyapunov exponent, signifying enhanced dynamical complexity. Subsequently, we devise a lightweight medical image encryption system leveraging the 1D-SAM and an innovative diffusion architecture, termed the plaintext-related and ciphertext feedback mechanism(PRCFM). This encryption system is a symmetric-key cryptosystem, eliminating the need for transmitting supplementary data beyond the secret keys to the recipient. Notably, the encrypted image maintains identical dimensions to its original counterpart and is fully recoverable. Complete simulation experiments were conducted on a personal computer equipped with MATLAB R2021a, OS Windows 11, 2.60GHz CPU and 16GB RAM. The experimental results indicate that our encryption system, employing a single permutation-diffusion round, efficiently encrypts a 512×512 image in approximately 0.2854 seconds. Leveraging the advantages of the PRCFM, our approach demonstrates superior plaintext sensitivity, achieving an average number of pixels changing rate (NPCR) of 99.6051 and a unified average changed intensity (UACI) of 33.4452. In summary, our work addresses key limitations of contemporary encryption frameworks, exhibiting acceptable performance in both encryption speed and security strength.

Learning how to explore spiritual aspects in encounters with patients with chronic pain: a pre-test post-test trial on the effectiveness of a web-based learning intervention

BackgroundIntegrating spiritual aspects into treatment plans can release essential resources for coping with chronic pain. However, some spiritual aspects may also induce distress and hinder the coping process. There is a lack of evidence regarding how to perform the clinical tasks of exploring spiritual aspects and of instruments assessing related competencies. Therefore, we developed a web-based learning module to provide education on the subject alongside corresponding assessment instruments. The module presents the InSpiRe (Integration of Spirituality and/or Religion in patient encounters) protocol. The instruments encompass cognitive, affective, and behavioral dimensions.MethodsThis paper aims to determine (i) the learning effects associated with completing the web-based spiritual-care learning module and (ii) the reliability and validity of the instruments employed. To address these aims, we conducted a pre-test/post-test trial with N = 32 randomly selected fourth-year medical students. During the pre-test, we assessed the students’ knowledge, attitudes, and self-efficacy regarding exploring spiritual aspects. For this purpose, we developed a short-answer knowledge test, an attitude questionnaire, and a self-efficacy scale. Additionally, the students explored spiritual aspects with a simulated patient portraying a person with chronic pain. Three trained raters evaluated the students’ performances using a self-developed scale. In the intervention phase, the students completed the 45-minute learning module on a personal computer. The module presented InSpiRe-related content as text and step-by-step video demonstrations, including hints that denote critical actions. The subsequent post-test was identical to the pre-test.ResultsThe internal consistency was suitable for all respective instruments, and there was an indication of solid validity of the performance test. After completing the spiritual care learning module, the students showed statistically significant increases in knowledge scores and significant positive shifts in their attitudes and levels of self-efficacy regarding exploring spiritual aspects. They also attained significantly higher performance scores in the same regard.ConclusionsCompleting the spiritual-care module is associated with meaningful learning effects on cognitive, affective, and behavioral dimensions related to exploring spiritual aspects, as demonstrated in the post-test conducted shortly after the intervention. Due to good reliability and validity scores, the self-developed instruments can be applied appropriately.

A Method for Speed Up the Allpass Transformation Algorithm

Two algorithms for calculating the phase transformation, which consists in calculating the outputs of a chain of phase links, are considered. The algorithms are based on the idea of synthesis of a dual phase link, which allows calculating the outputs of a cascade of two-phase links in one pass. To synthesize dual phase links, the representation of digital filters by the space state method is used. The proposed algorithms are implemented in the C language, and they are compared with the direct form of implementation of the phase transformation. During the experiments, the speed of calculating the chain of phase links on a personal computer with an Intel Core i7-37700 processor was estimated using the profiler built into the Visual Studio environment. The results showed that both algorithms allow accelerating the calculation of the chain of phase links by 1.3 and 1.8 times, respectively.

Intellectual Capital: Revisiting an Analytical Model

The world’s economy is experiencing important changes brought on by diverse factors, namely technological advancements, the appearance and diffusion of personal computers, high-speed telecommunications, and the Internet. These technological changes have influenced the corporate environment, with recent decades denominated as the information economy, the digital economy, the economy of knowledge, a risk society, and the age of quality and innovation. To designate the key concept of the new economic era as “intellectual capital” implies a classification and evaluation effort in order to proceed with its generalization. In today’s world, the study of a model capable of adding explanatory diversity to intellectual capital is very relevant. We observed a true panoply of concepts in the analyzed models based on a literature review. The conceptual evolution during recent decades has motivated many investigations in this field, resulting from the phenomenon of globalization, growing technological innovation, and the observation of significant disparities between the market value and the accounting value of companies. This article describes an investigation carried out, presenting an explicative model of intellectual capital based on four distinct patterns, which are the aggregating factors of the existing conceptual diversity. We present the identification of a model with two axes, x (the type of knowledge, from tacit to explicit) and y (the capital of knowledge, from human to structural), which represents the conceptual diversity mirrored in four quadrants resulting from the research carried out with an initial exploratory study and two following studies with 45 and 72 specialists. In this article we analyze the Martins model, which proves to be essential for systematizing and mapping the dimensions that intellectual capital includes. This model can be used to identify the different aspects of intellectual capital in an organization and thus contribute to its understanding, optimization and good management.

Modeling the effect of land-use change on runoff water quality in the urban watershed: a case study of Settat city, Morocco

ABSTRACT The purpose of this study is to create a model of the quantity and quality of runoff from the urban watershed. The modeling was performed using a personal computer stormwater management model (PCSWMM) tool and was based on washoff and buildup for total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) measured in the field. In addition, low impact development (LID) was used under four different scenarios to improve runoff control of the urban hydrologic cycle and reduce pollutant concentrations. Model performance was analyzed using the R2 and NSE goodness-of-fit indices. Thus, three typical rainfall events, as well as field measurement parameters (TSS, TN, and TP), were used for the model's calibration and validation. The base scenario quantified the runoff volume and pollutant load without any intervention in the runoff process control. Scenarios S2 (BR: bioretention) and S3 (PP: permeable pavement) contributed, separately, in reducing runoff and pollutant load but with relatively small percentages. In addition, the results show that scenario S4 (BR and PP) has the most significant impact on flow reduction, by about 10% compared with the base scenario, as well as on the pollutant load reduction, by about 31, 29, and 40% for the parameters TSS, TN, and TP, respectively.

Numerical search for the effective thermal conductivity of cracked media

Spacecraft parts accumulate damage during operation and defects that are invariably present even in new designs may grow. This leads to changes in the behavior of individual parts of the space vehicle and, consequently, to the risk of fracture. A more accurate assessment of spacecraft safety requires internal defects to be included in the material models under consideration. One of the main hazardous effects on space objects is multiple temperature heating and cooling due to periodic action of solar rays. This paper presents a study of thermal conduction of media containing cracks. It is carried out with the help of a technique developed by the authors to determine the effective thermal conductivity of materials and based on approximate numerical solution of the steady-state thermal conduction problem for a three-dimensional medium with cracks by the boundary element method. This technique allows to obtain the distribution of the temperature field and heat flux density at any point of the body under consideration, as well as to calculate the effective parameters of materials with high accuracy at relatively low calculation time using ordinary personal computers of average power. The basis of the numerical method presented in this paper is the decomposition of the desired solution into a series of some pre-calculated analytical solutions of the heat conduction equations. The dependence of the effective thermal conductivity on the density of thermally insulated cracks was considered. The formula of this dependence is proposed. Verification of the proposed methodology was carried out by comparing the numerical results of a number of problems with the results of other authors.

Comparative Study of Fast Optimization Method for Four‐Intensity Measurement‐Device‐Independent Quantum Key Distribution Through Machine Learning

AbstractThe four‐intensity protocol for measurement‐device‐independent (MDI) quantum key distribution (QKD) is renowned for its excellent performance and extensive experimental implementation. To enhance this protocol, a machine learning‐driven rapid parameter optimization method is developed. This initial step involved a speed‐up technique that quickly pinpoints the worst‐case scenarios with minimal data points during the optimization phase. This is followed by a detailed scan in the key rate calculation phase, streamlining data collection to fit machine learning timelines effectively. Several machine learning models are assessed—Generalized Linear Models (GLM), k‐Nearest Neighbors (KNN), Decision Trees (DT), Random Forests (RF), XGBoost (XGB), and Multilayer Perceptron (MLP)—with a focus on predictive accuracy, efficiency, and robustness. RF and MLP were particularly noteworthy for their superior accuracy and robustness, respectively. This optimized approach significantly speeds up computation, enabling complex calculations to be performed in microseconds on standard personal computers, while still achieving high key rates with limited data. Such advancements are crucial for deploying QKD under dynamic conditions, such as in fluctuating fiber‐optic networks and satellite communications.

Trimodal Watch-Type Wearable Health Monitoring Device

In the domain of healthcare, wearable health monitoring devices have emerged as essential tools for the advancement of patient health tracking. These devices facilitate the provision of real-time medical data to clinicians, enabling early diagnosis, timely intervention, and enhanced management of individual health. This study introduces an innovative trimodal wearable health monitoring device in the form of a wristwatch. The device integrates a breath analyzer for the assessment of gaseous phase biomarkers, a sweat analyzer for the evaluation of aqueous-phase biomarkers, and an infrared sensor for the measurement of body temperature in the optical phase. Engineered on a compact 3 cm × 3 cm printed circuit board, the device has been optimized for wearability, power efficiency, and seamless integration with both wired and wireless charging and communication systems. Furthermore, custom software applications, designed for both Windows and Android platforms, have been developed to facilitate intuitive data visualization and storage on personal computers and smartphones. Empirical results from real-time chemical testing substantiate the device’s efficacy and potential as an advanced solution for wearable health monitoring.

ICT in biology education: teachers’ readiness and implementation challenges in the context of Bangladesh

Information and Communication Technology (ICT) is commonly employed in biology classes to facilitate students' comprehensive comprehension of biological processes and enable them to see living phenomena. The purpose of the study was to explore the use of ICT in enhancing the teaching and learning process of biology in the secondary schools of Bangladesh. In our study, sequential explanatory mixed method design has been followed. Data was collected from purposively selected ten secondary schools of Dhaka city. The study reveals that teachers have a positive attitude towards incorporating ICT in biology lessons and possess operational understanding of data processing tools and online browsing. Nevertheless, it also emphasizes the fact that teachers are devoid of personal computers in their houses and have restricted availability to school computers. Furthermore, the existing curriculum and teachers' guides lack adequate instructions for integrating ICT into biology lectures. The study also suggests that the process of developing ICT-based curriculum is complicated, which deters teachers from incorporating ICT into their classes. Furthermore, there is a limited availability of educational materials related to ICT in the Bangla language. This study recommends continuous in-servicing training on ICT to teachers, interest free loan to teachers for purchasing laptops, developing interactive biology educational ICT contents in Bangla and include specific instructions in the curriculum and teachers’ guide on how to use ICT in biology classes. These findings have important implications for policy makers, educators, and researchers who are dedicated to expanding the use of ICT in education.

Wastewater flooding risk assessment for coastal Communities: Compound impacts of climate change and population growth

The study introduces a wastewater modeling framework that evaluates the compound impacts of intense rainfall, groundwater infiltration, sewer aging based roughness and population growth on wastewater systems. It integrates property and city-level flooding risk assessment and wastewater treatment plant (WWTP) capacity analysis into a single methodological approach. The framework applied to the coastal city of Charlottetown, whose population increased from 30,887 in 1981 to 42,440 in 2023, but the wastewater system did not expand accordingly, resulting in frequent sewer backups, street and basement flooding, as witnessed during the extreme wet weather event of September 2, 2021. Using PCSWMM (Personal Computer Storm Water Management Model), the study assessed that the city-wide wastewater flooding risk in Charlottetown, based on 2023 population data and historical IDF curves, affects 13.31% of the network during a 2-year storm and 18.38% during a 100-year storm. These risks increase to 14.5% and 22.6% under future IDF scenarios, reaching 17.89% and 26.4% by 2060 with projected population growth. The WWTP capacity is exceeded by 27.8% during peak wet weather flows from a 2-year storm and by 86.3% during a 100-year storm, based on 2023 population and historic IDFs. Under future IDF scenarios for 2060 population, exceedances rise to 103.6% and 169.1% respectively, for a 2-year and 100-year storm. Basement flooding risk affects 13.35% of basements during a 2-year storm and 18.31% during a 100-year storm, for 2023 population and historic IDFs. Future IDF scenarios indicate risk increasing to 17.77% and 25.80% by 2060 for a 2-year and 100-year storm respectively. The hydraulic modeling results indicate that GWI is not currently impacting the study area, nor is it expected to in near future, because the groundwater table is over 10 m deep, while wastewater pipes are no deeper than 6 m. The framework and study have significant social implications and benefits, including protecting public health, enhancing the resilience of urban infrastructure, and safeguarding the environment, ultimately improving the quality of life for residents in coastal communities like Charlottetown.

Small Public Exponent Brings More: Improved Partial Key Exposure Attacks against RSA

Let (N,e) be a public key of the RSA cryptosystem, and d be the corresponding private key. In practice, we usually choose a small e for quick encryption. In this paper, we improve partial private key exposure attacks against RSA with a small public exponent e. The key idea is that under such a setting we can usually obtain more information about the prime factor of N and then by solving a univariate modular polynomial with Coppersmith's method, N can be factored in polynomial time. Compared to previous results, we reduce the number of d's leaked bits needed to mount the attack by log_2 (e) bits. Furthermore, our experiments show that for 1024-bit N, our attack can achieve the theoretical bound on a personal computer, which verified our attack.

Implementation of Optical Coherent Communication System between Two Computers

This work represents implementation and investigation of optical coherent communication system between two computers. A single mode optical fiber is selected as transmission medium. The data are sent via the RS-232 standard interface with a bit rate of 9.6 kbps from personal computer (PC1) by line receive to convert the data from electrical levels (-12/+12 V) into TTL level (0/5 V). The modulation of this data was accomplished by internal modulation using laser diode type (HFCT-5208M) 1310 nm wavelength. The optical D-coupler was used to combine the optical signal that come from laser source with optical signal of laser local oscillator (OTS-304XI) at 1310/1550 nm wavelength to obtain coherent (homodyne and heterodyne) detection respectively. A PIN photodetector (HFCT-5208M) is used. Calculations of Signal to Noise Ratio (SNR) and Bit Error Rate (BER) for coherent detection were measured at different length of the optical fiber. Result show that high SNR and low BER for heterodyne detection than for homodyne detection.

Case study of simplified reverberation time measurement under multiple conditions using a sound level meter

Recent advancements in the computational capacity of sound level meters have facilitated the simultaneous recording of diverse calculation results and waveform recording data. Traditionally, reverberation time determination entailed manually adjusting a linear regression line to the reverberation decay curve derived from recorded sound levels, followed by reverberation time computation based on the gradient of said line. However, automated techniques have made reverberation time calculation via a sound level meter feasible. This paper discusses a case study evaluating the efficacy and considerations of simplified reverberation time measurements conducted across various conditions, encompassing scenarios with multiple sound sources and diverse indoor environments. The study leveraged recorded data from a sound level meter and employed automated methods simulated on a personal computer.

Combinative model compression approach for enhancing 1D CNN efficiency for EIT-based Hand Gesture Recognition on IoT edge devices

Tiny Machine Learning is rapidly evolving in edge computing and intelligent Internet of Things (IoT) devices. This paper investigates model compression techniques with the aim of determining their compatibility when combined, and identifying an effective approach to improve inference speed and energy efficiency within IoT edge devices. The study is carried out on the application scenario of Hand Gesture Recognition (HGR) based on Electrical Impedance Tomography (EIT), which involves complex signal processing and needs real-time processing and energy efficiency. Therefore, a customized 1-Dimensional Convolutional Neural Network (1D CNN) HGR classification model has been designed. An approach based on strategically combining model compression techniques was then implemented resulting in a model customized for faster inference and improved energy efficiency for IoT embedded devices. The model size became compact at 10.42 kB, resulting in a substantial size reduction of 98.8%, and an inference gain of 94.73% on a personal computer with approximately 8.56% decrease in accuracy. The approach of combinative model compression techniques was applied to a wide range of edge-computing IoT devices with limited processing power, resulting in a significant improvement in model execution speed and energy efficiency for these devices. Specifically, there was an average power consumption gain of 52% for Arduino Nano BLE and 34.05% for Raspberry Pi 4. Inference time was halved for Arduino Nano BLE Sense, Nicla Sense, and Raspberry Pi 4, with a remarkable gain of 94% for ESP32.

A threat modeling framework for IoT-Based botnet attacks

Internet of Things (IoT) devices are much closer to users than personal computers used in traditional computing environments. Due to prevalence of IoT devices, even if they are compromised and used in attacks, it is difficult to detect and respond to them. Currently, there has been extensive research on threat modeling for cyberattacks. However, there remains a significant gap in research concerning threat modeling for attacks specially targeting IoT devices within the fifth-generation communication environment. In this paper, we present IoT Targeting-Threat Modeling(I3TM) framework established by analyzing botnets that are appeared before 2021 such as Mirai, Pink etc. Through this framework, we identify tactics and techniques to respond to the attacks. Using the identified tactics and techniques from our proposed framework, we can promptly respond to the newly detected attacks. We constructed a Threat Modeling Framework Keyword-Based Metrics to show extracted keywords from reports, academic papers, and white paper that identifies the features of botnet. We also provide an objective way to apply those keywords to the framework. Our framework is organized to analyze the attack process of botnets that may occur against IoT. The framework derives execution for each tactic for objective analysis based on keywords. In the validation for the framework, I3TM identified eight Tactics from Medusa botnet. If the application of the I3TM framework is continuously accumulated, a baseline of similar attack methods and data will be formed. In future research, we are planning to append mitigations for the attacks targeting IoT to the I3TM framework.

Feasibility of a digital palliative care intervention (Convoy-Pal) for older adults with heart failure and multiple chronic conditions and their caregivers: a waitlist randomized control trial

BackgroundAlthough older adults with heart failure (HF) and multiple chronic conditions (MCC) frequently rely on caregivers for health management, digital health systems, such as patient portals and mobile apps, are designed for individual patients and often exclude caregivers. There is a need to develop approaches that integrate caregivers into care. This study tested the feasibility of the Social Convoy Palliative Care intervention (Convoy-Pal), a 12-week digital self-management program that includes assessment tools and resources for clinical palliative care, designed for both patients and their caregivers.MethodsA randomized waitlist control feasibility trial involving patients over 65 years old with MCC who had been hospitalized two or more times for HF in the past 12 months and their caregivers. Descriptive statistics were used to evaluate recruitment, retention, missing data, self-reported social functioning, positive aspects of caregiving, and the acceptability of the intervention.ResultsOf 126 potentially eligible patients, 11 were ineligible and 69 were deceased. Of the 46 eligible patients, 31 enrolled in the trial. Although 48 caregivers were identified, only 15 enrolled. The average age was 76.3 years for patients and 71.6 years for caregivers, with most participants being non-Hispanic White. Notably, 4% did not have access to a personal mobile device or computer. Retention rates were 79% for intervention patients, 57% for intervention caregivers, and 60% for control participants. Only 4.6% of survey subscales were missing, aided by robust technical support. Intervention patients reported improved social functioning (SF-36: 64.6 ± 25.8 to 73.2 ± 31.3) compared to controls (64.6 ± 27.1 to 67.5 ± 24.4). Intervention caregivers also reported increased positive perceptions of caregiving (29.5 ± 5.28 to 35.0 ± 5.35) versus control caregivers (29.4 ± 8.7 to 28.0 ± 4.4). Waitlist control participants who later joined the Convoy-Pal program showed similar improvements. The intervention was well-rated for acceptability, especially regarding the information provided (3.96 ± .57 out of 5).ConclusionsRecruiting informal caregivers proved challenging. Nonetheless, Convoy-Pal retained patients and collected meaningful self-reported outcomes, showing potential benefits for both patients and caregivers. Given the importance of a patient and caregiver approach in palliative care, further research is needed to design digital tools that cater to multiple simultaneous users.Trial registrationClinicalTrials.gov Identifier NCT04779931. Date of registration: March 3, 2021.

Arterial vascular complications predictive score in extrasystolic arrhythmia "EX-prognosis".

The aim of this study was the creation of an optimal model for predicting arterial vascular complications in patients with extrasystolic arrhythmia. A single-center prospective study was performed with involving 634 patients with supraventricular or ventricular extrasystoles (ES) of 700 or more per 24 hours. The control group consisted of 106 people with ES less than 700 per 24 hours. The main and control groups were initially equivalent in anthropometric criteria and concomitant pathology. The list of examinations included laboratory methods (including lipid profile, coagulograms), as well as instrumental studies (transthoracic and/or transesophageal echocardiography (EchoCG), Doppler ultrasound of the brachiocephalic arteries and arteries of the lower extremities, 24-hours ECG monitoring, according to the indications - computed tomography or magnetic resonance imaging of the brain, coronary angiography, stress echocardiography. Prospective observation of patients performed for 1 year after the initial examination. Combined end points: development of arterial vascular complications - stroke, myocardial infarction, distal arterial embolism of other locations. We studied the data on identified complications. Next, we built models for predicting complications in various ways: Decision Tree; Bootstrap Forest; Boosted Tree; Neural Boosted; Support Vector Machines; Fit Stepwise; Nominal Logistic; Generalized Regression Lasso; Generalized Regression Forward Selection; Generalized Regression Pruned Forward Selection; Generalized Regression Elastic Net; Generalized Regression Ridge. To assess the quality of the models and compare them we used cross-validation with 30 replications. The highest profit values with minimal values of false positive results were obtained for the Bootstrap Forest model. Basing on this model, we created arterial vascular complications predictive score in extrasystolic arrhythmia "EX-prognosis" that included the following parameters: atheroma type III in carotid arteries - 3 points; age 69+ years old - 2 points; ES appearing before transmitral blood flow peak in cardiac cycle 700 and more per 24 hours - 1 point; carotid arteries stenosis, non-significant - 1 point. If total number is 3 and more points, the risk of arterial vascular complications within 1 year is high. We recommend to use the scale "EX-prognosis" in the clinical practice. For a quick assessment of the total risk, it is optimal to implement the risk14.exe program - calculator - developed by us for a personal computer, based on this scale.

Contactless Printing of Food Micro-Particles Controlled by Ultrasound

Traditional food 3D printing technology, which primarily relies on mechanical control, often faces challenges such as low resolution, stringent material requirements, limited flexibility, and cumbersome equipment. To overcome these limitations, we developed an innovative food 3D printing method utilizing ultrasonic phased arrays and subsequently designed a contactless printing device employing this advanced technology. The device effectively manipulates the phase and amplitude of the ultrasonic phased array to focus the sound field on a specific location. We have successfully demonstrated preliminary control over the suspension of small food particles, including popcorn, chocolate, honey, and marshmallows, using this apparatus. Following this, popcorn particles were selected for detailed practical printing and further analysis.Additionally, we established a software platform, Ultr_printing, based on Ultraino, for intelligent simulation and control of the printing process. Leveraging FPGA and Arduino controllers, this setup facilitates rapid signal transmission from personal computers to sensors, ensuring quick and adaptable movement of suspended particles. Experimental results confirm that the device consistently controls the food particles, irrespective of their motion state. Notably, it achieves a printing precision of 0.16 mm when handling popcorn particles measuring 1.5 mm in diameter. The process, entirely contactless and free from contamination, preserves the original flavor of the food particles. This technology is particularly effective for high-precision printing of micro-scale shapes and offers considerable benefits in assembly and precision manufacturing.

Adaptive Current Angle Compensation Control Based on the Difference in Inductance for the Interior PMSM of Vehicles

Achieving good performance in terms of a fast and accurate maximum torque per ampere (MTPA) control method depends on both accurate parameter estimation and a sophisticated control strategy. However, it often requires a complex and long computational process. This paper proposes an efficient control method using the relationship of torque and current angle for maximum torque per ampere control of the interior permanent magnet synchronous motor (IPMSM) for vehicle application. It was found that it is not necessary for the control method to determine the inductance in the d-q axes; the identification of the difference between each axis is enough. Furthermore, this paper presents a simple and effective procedure to estimate the difference in inductance online, where the linear iron loss calculation method is also designed to support the above process. The proposed control method was experimentally validated on a 5 kW prototype by a TMS320F28335 microcontroller and DSPACE synchronized with a personal computer. The results show that the control process has faster and more accurate performance than the conventional method.

Two-dimensional hyperchaos-based encryption and compression algorithm for agricultural UAV-captured planar images.

This study presents an approach that integrates compressed sensing technology with two-dimensional hyperchaotic coupled Fourier oscillator systems (2D-HCFOS) to address the challenge of slow encryption speeds in agricultural unmanned aerial vehicles (UAVs). The primary challenge in enhancing encryption speed lies in the limited capacity inherent in traditional chaotic-based systems and the computational complexity of their processes. The 2D-HCFOS utilizes a complex two-dimensional hybrid chaotic system, which significantly enhances the security of agricultural UAV image data. Notably, the image encryption process is performed on a personal computer connected to the drone, ensuring efficient processing. By integrating advanced Fourier series and nonlinear coupled oscillators, the model surpasses existing chaotic-based methods, improving both the pseudo-randomness and robustness of encryption. Additionally, incorporating Bonouille functions into the discrete cosine transform (DCT) domain results in a sparser measurement matrix, which is essential for efficient encryption on personal computers. The effectiveness of 2D-HCFOS in securely encrypting agricultural drone images has been rigorously validated through simulations and analytical evaluations using sophisticated row, rotation, and matrix encryption techniques. The improved security performance is further verified by comparative analysis. Compared with other models, the Lyapunov index of 2D-HCFOS is 15.1039, and the sample entropy is 2.4987, indicating that it possesses superior chaotic performance and encryption reliability.