Electrical Engineering Research Articles

Systematic Review of AI-Assisted MRI in Prostate Cancer Diagnosis: Enhancing Accuracy Through Second Opinion Tools

Background: Prostate cancer is a leading cause of cancer-related deaths in men worldwide, making accurate diagnosis critical for effective treatment. Recent advancements in artificial intelligence (AI) and machine learning (ML) have shown promise in improving the diagnostic accuracy of prostate cancer. Objectives: This systematic review aims to evaluate the effectiveness of AI-based tools in diagnosing prostate cancer using MRI, with a focus on accuracy, specificity, sensitivity, and clinical utility compared to conventional diagnostic methods. Methods: A comprehensive search was conducted across PubMed, Embase, Ovid MEDLINE, Web of Science, Cochrane Library, and Institute of Electrical and Electronics Engineers (IEEE) Xplore for studies published between 2019 and 2024. Inclusion criteria focused on full-text, English-language studies involving AI for Magnetic Resonance Imaging (MRI) -based prostate cancer diagnosis. Diagnostic performance metrics such as area under curve (AUC), sensitivity, and specificity were analyzed, with risk of bias assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Results: Seven studies met the inclusion criteria, employing various AI techniques, including deep learning and machine learning. These studies reported improved diagnostic accuracy (with AUC scores of up to 97%) and moderate sensitivity, with performance varying based on training data quality and lesion characteristics like Prostate Imaging Reporting and Data System (PI-RADS) scores. Conclusions: AI has significant potential to enhance prostate cancer diagnosis, particularly when used for second opinions in MRI interpretations. While these results are promising, further validation in diverse populations and clinical settings is necessary to fully integrate AI into standard practice.

The European Unified Patent Court and non-practicing entities: a year of early evidence

ABSTRACT Traditionally, the debate over Non-Practicing Entities (NPEs) has centred on U.S. patent law, as this is the legal arena where most NPE lawsuits occur. However, the establishment of the European Unified Patent Court (UPC) has drawn increased attention from European policymakers, as it has the potential to escalate NPE activity by enhancing the litigation value of patents in Europe. In this article, I conduct an analysis of all infringement cases filed during the first year of operation of the UPC. I identify cases initiated by NPEs and collect details of the patents litigated and the companies involved. The main findings suggest that the UPC could become an attractive venue for NPEs to litigate their patents. NPEs initiate 13.0% of all cases, with their activity concentrated exclusively in the latter half of the period (December 2023 – May 2024), during which they represent 24.6% of total cases and 43.0% in the Electrical Engineering sector. In terms of patent characteristics, NPEs tend to litigate patents of lower quality than those pursued by other types of litigants.

Tunable electronic and optoelectronic characteristics of two-dimensional β-AsP monolayer: a first-principles study.

Two-dimensional (2D) semiconductors have attracted a great deal of interest from the electrical engineering community due to their intriguing electronic properties. In this study, we have systematically investigated the electronic and optoelectronic properties of β-AsP monolayers by first-principles calculations combined with strain engineering. The results show that the β-AsP monolayer has a suitable indirect bandgap and a strain-tunable electronic structure. On this basis, the designed two-electrode photodetector based on β-AsP monolayer exhibits a strong photoelectric response in the near-ultraviolet region, and the maximum photocurrent can reach 74a02 per phonon under the applied bias voltage of 1 V. In particular, the strain engineering not only improves the photoelectric performance of the β-AsP-based photodetector, but also adjusts its photodetection range. These findings suggest that β-AsP monolayers are ideal candidates for the development of near-ultraviolet photodetectors and optoelectronic devices.

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

Stretchable and body conformable electronics for emerging wearable therapies

AbstractWearable therapy represents a research frontier where material science, electrical engineering, and medical disciplines intersect, offering significant potential for remote and portable healthcare. Unlike conventional approaches that rely on rigid materials, the ability to stretch is crucial for therapeutic devices to achieve enhanced mechanical adaptability. Moreover, the conformable integration of these devices into the body is pivotal in establishing reliable interfaces for long‐term treatment. These emerging devices provide an attractive platform for developing new therapeutic protocols that do not disrupt daily activities. This review comprehensively overviews recent progress in stretchable and body‐conformable electronics for wearable therapeutic applications. The discussion begins with the design and fabrication of these devices through structural designs and material innovation. The therapeutic mechanisms adopted by these devices are then systematically explored. Furthermore, the article delineates the crucial characteristics of wearable therapeutic devices, such as biocompatibility, secure skin attachment, and effective moisture management. This review article is poised to inspire innovative device designs and treatment protocols for future medical technology.

Toxic Effects in Subsequent Generations from Sex-Dependent Exposure to 2,3′,4,4′,5-Pentachlorobiphenyl (PCB 118) on Danio rerio

The results of an experiment on oral exposure of polychlorinated biphenyl (PCB) 118 into fish Danio rerio (Hamilton, 1822) (F0) with food at calculated doses of 5, 20, 80 μg/ind. are presented. In the first generation F1, there is a decrease in survival rate and a shift in the sex ratio, predominantly towards females. In the second generation F2, the same effects are noted as in F1, but they are not as pronounced. It has been hypothesized that the effects seen in the F2 generation may be caused by epigenetic mechanisms, which are still poorly understood. It is possible that the feminization of animal populations and a decrease in their survival rate are very strong factors in reducing the populations of living organisms, including humans, especially near sites of distribution of PCBs. It is necessary to study epigenetic mechanisms in order to develop measures to eliminate and prevent problems with the biotic degradation and depopulation of fish exposed to PCBs in the sites that arise as a result of the improper disposal of electrical engineering waste containing PCBs.

Power Quality Analysis of a Microgrid-Based on Renewable Energy Sources: A Simulation-Based Approach

At present, microgrids (μGs) are a focal point in both academia and industry due to their capability to sustain operations that are stable, resilient, reliable, and of high power quality. Power converters (PCs), a vital component in μGs, enable the decentralization of power generation. However, this decentralization introduces challenges related to power quality. This paper introduces a μG model, based on the IEEE 14-bus distribution system, with the objective of investigating power quality when the μG is operating in conjunction with the conventional power grid. The μG model was developed using MATLAB-Simulink®, a tool specialized for electrical engineering simulations. The results obtained undergo thorough analysis and are compared with the compatibility levels set by the IEEE-519 standard. This method enables a precise evaluation of the μGs’ capacity to maintain acceptable power quality levels while interconnected with the conventional power grid. In conclusion, this study contributes significantly to the field of μGs by providing a detailed and quantitative assessment of power quality. This will assist in the design and optimization of μGs for effective implementation in real-world electric power systems.

Occupancy-based Energy Management System in Campus Building: A Case Study in Electrical Engineering Department Building, ITN Malang

Building energy management systems provide an effective method for energy saving. An occupancy-based energy management system considers the occupants' behavior that affects energy consumption. This paper presents the investigation of different scenarios based on the occupancy to control the energy consumption in the Electrical Engineering Department Building, ITN Malang. The results show that switching off the appliances when the occupants go home in the afternoon reduces the monthly energy consumption by 33.95%. The result indicates that the occupants' awareness regarding energy saving has recently been low. Thus, the occupancy sensor and automatic time scheduling for the appliance control are suggested to be installed.

Integral Sliding Mode‐Composite Nonlinear Feedback Control Strategy for Microgrid Inverter Systems

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Advancing Electrical Engineering with Biomass-derived Carbon Materials: Applications, Innovations, and Future Directions.

The ongoing global shift towards sustainability in electrical engineering necessitates novel materials that offer both ecological and technical benefits. Biomass-derived carbon materials (BCMs) are emerging as cornerstones in this transition due to their sustainability, cost-effectiveness, and versatile properties. This review explores the expansive role of BCMs across various electrical engineering applications, emphasizing their transformative impact and potential in fostering a sustainable technological ecosystem. The fundamentals of BCMs are investigated, including their unique structures, diverse synthesis procedures, and significant electrical and electrochemical properties. A detailed examination of recent innovations in BCM applications for energy storage, such as batteries and supercapacitors, and their pivotal role in developing advanced electronic components like sensors, detectors, and electromagnetic interference shielding composites has been covered. BCMs offer superior electrical conductivities, tunable surface chemistries, and mechanical properties compared to traditional carbon sources. These can be further enhanced through innovative doping and functionalization techniques. Moreover, this review identifies challenges related to scalability and uniformity in properties and proposes future research directions to overcome these hurdles. By integrating insights from recent studies with a forward-looking perspective, this paper sets the stage for the next generation of electrical engineering solutions powered by biomass-derived materials, aligning technological advancement with environmental stewardship.

The econophysical model of innovation diffusion

Analysis and evaluation of innovation efficiency require the development of tools to model their dissemination process within the industry. This paper presents a model of innovation diffusion based on physical approaches, describing stages of accelerating and decelerating growth. An exponential growth is described using a diffusion model, while a logarithmic one employs an electrical engineering model. The paper presents the correspondence of physical parameters with their economic counterpart: size of a company; characteristic of speed of information exchange between firms; company’s willingness to innovate; inter-firm influence and the breakthrough level of innovation. The theoretical model obtained was tested on historical data of innovation implementation in the fuel and energy complex, followed by adjustments of coefficients depending on the branch of innovation implementation. The developed model is applicable for describing the process of innovation dissemination in any industry in the country, as well as for investment and business planning in companies and decision-making on investments in innovation projects. When applied in industries with low levels of innovation activity, an increase in the level of high-tech production and the share of organizations implementing technological innovations is predicted. Using the example of Russia’s fuel and energy sector, rising in the technological level of enterprises and a decrease in import dependence are forecasted.

EV Charging Prediction in Residential Area Based on SE‐GRU‐MA Model Consider Multi‐Source Data Feature Mining

The number of electric vehicle (EV) in residential areas is growing rapidly, resulting in large‐scale charging of EVs connected to the distribution network. This poses a challenge to the safe and stable operation of the distribution network. In order to cope with this challenge, it is crucial to achieve accurate EV charging load prediction. However, current researches on EV charging load prediction suffer from insufficient data feature mining and lower prediction accuracy. To address this issue, this paper proposes a SE‐GRU‐MA residential EV charging load prediction method that incorporates multi‐source data feature mining. The proposed method employs a multi‐source data feature mining approach based on Pearson correlation analysis, which enhances the training efficiency and prediction accuracy of the prediction model. Additionally, this study develops a prediction model based on SE‐GRU‐MA hybrid network to achieve accurate EV charging load prediction. Simulation cases on actual history data validate that the proposed feature mining method can effectively promote prediction accuracy, and proposed SE‐GRU‐MA prediction model exhibits superior prediction capability in comparison to existing models. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Effect of Project-Based Learning Model on Creativity and Learning Outcomes of Basic Electrical Engineering

This study aims to determine the effect of project-based learning models on creativity and learning outcomes of Electrical Installation and Power Engineering students in the Basic Electrical Engineering subject in class XI of SMKN 1 Airmadidi. This study used an experimental method with a post-test-only control group design. The instruments used included learning outcome tests and creativity questionnaires. The results showed a significant difference in the learning outcomes of Basic Electrical Engineering between students who were involved in learning using project-based models and those who followed conventional methods. This indicates that applying project-based learning models substantially affects the learning outcomes of Basic Electrical Engineering in Class XI of SMKN 1 Airmadidi with a ttable value < tcount or 4.10 < 6.773. The project-based model also shows the level of creativity between students who undergo learning with a project-based approach and those who use conventional methods. These findings indicate a significant effect of the project-based learning model on student learning creativity in Class XI of SMKN 1 Airmadidi with a ttable value < tcount or 4.10 < 6.418.

Modeling Borehole Resistivity Logs with Exponentially Graded Multilayered Soil Inversion for Electrical Engineering Applications

In this paper, we present the application of a special soil resistivity model, the Exponentially Graded Multilayered Soil model, to the interpretation of Borehole Resistivity Logging surveys. The model, which was recently introduced by the authors, offers an alternative to the interpretation provided by constant resistivity layer models. The model is applied to synthetic soil surveys as well as to a real survey that is not satisfactorily interpreted using conventional models. This model aids in the design and calculation of grounding systems in electrical engineering, providing an alternative to calculations performed by traditional layered models.

Wrap‐Around String‐Like ToF and Self‐Capacitance Combined Sensor for Robots

Collaborative robots are becoming popular because they can operate without safety fences and can work in close proximity to humans. Proximity and tactile sensors on the robot's surface are important safety measures for existing robots. In this paper, we propose a string‐like ToF and self‐capacitance combined sensor that can be easily wrapped around various types of existing robots. The sensor can be freely connected to other sensors, and the length of the connected sensors attached can be adjusted depending on the shape of the robot. Prototype sensors were fabricated, and four connected sensors were wrapped around the robotic arm. Sensors on the robot's surface can detect objects within the proximity range and determine contact. In addition, a robotic arm with sensors can be controlled in real‐time using measured data from the sensors. It was confirmed that the proposed sensor can be used for proximity and tactile sensing on existing robots. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

The Analysis of Applied Innovative Mechatronics Technology in Intelligent Driving - A Case Study of New-Energy Vehicles' Development in Mainland China

Abstract. The interdisciplinary field of mechatronics, which amalgamates elements of mechanical, electrical, computer, and control engineering, has fundamentally transformed the automotive industry. This transformative influence is evident in the development of advanced vehicular functionalities such as Automatic Fuel Filling Systems, Car Attitude Control, Antilock Brake Systems (ABS), and Electronic Stability Programs (ESP), as well as in the advent of vehicles equipped with semi-active suspensions. The integration of mechatronics has not only enhanced vehicle safety, efficiency, and performance but has also positioned itself as a cornerstone for the burgeoning electric vehicle (EV) market, particularly in China. Chinese companies, leveraging extensive smart factory and automation technologies, have consequently secured a dominant stance in the global EV landscape, capturing a staggering 60% market share. This paper explores the multifaceted applications of mechatronics in the automobile industry of industrialized nations, with a special focus on its pivotal role in China's technological ascendancy in automotive manufacturing. Through an exploration of practical applications including IoT integration and collaborative robotics, this study underscores the transformative potential of mechatronics in redefining automotive production and operation, propelling the industry toward unprecedented levels of innovation and efficiency.

An Alternative Approach for Evaluating Induced and Contact Currents for Compliance with Their Exposure Limits (100 kHz to 110 MHz) in IEEE Std C95.1-2019.

The Institute of Electrical and Electronics Engineers establishes exposure reference levels (ERLs) for electric fields (E-fields) (0-300 GHz) and both induced (IIND) and contact currents (ISC) (<110 MHz) in its standard, IEEE Std C95.1™-2019 (IEEE C95.1). The "classical" scenarios addressed in IEEE C95.1 include a free-standing, grounded "reference" person (IIND) or an ungrounded reference person in manual contact with an adjacent grounded conductor (ISC), each exposed to a vertically oriented E-field driving the currents. The ERLs for current from 100 kHz to 110 MHz were established to limit heating in the finger (from touch), ankle (IIND), and wrist (ISC from grasp contact), specifying the 6-min average specific absorption rate (SAR, W kg-1) as the dosimetric reference limit (DRL); whole-body E-field ERLs are 30-min averages. The DRLs were established assuming a default "effective" local cross-section (9.5 cm2) and consistent with a composite tissue conductivity of ~0.5 S m-1. A previous publication described the misalignment of the ERLs for E-fields with the ERLs for IIND (which extends to ISC) and also proposed a ramped E-field ERL from 100 kHz to 30 MHz. For the frequency range 100 kHz to 110 MHz, this paper proposes temperature increase (ΔT) in ankle and wrist as the preferred effect metric associated with IIND and ISC; applying the E-field ERLs as surrogates for limits to these currents; and adopting the proposed ramp. The analysis of ΔT is based on the tissue mix in realistic anatomic depictions of ankle and wrist cross-sections; relevant tissue properties posted online; published tissue perfusion data; and anthropometric data on a large sample of male and female adults in the US military, allowing an estimate of effects over a range of body size. To evaluate ΔT versus frequency and time, the Penne bioheat equation was adapted with convective cooling from arterial blood as the lone cooling mechanism. The analysis revealed that IINDs and ISCs induced by ERL-level E-fields produce SARs in excess of the local DRLs (in some cases far exceed). Calculations of time to ΔT of 5 °C, reflective of a potentially adverse (painful) response, resulted in worst-case times for effects in the ankle on the order of minutes but on the order of 10s of s in wrist. Thus, compliance with the E-field ERL, as assessed as a 30-min whole-body average is incompatible with the time course of potentially adverse effects in ankle and wrist from IIND and ISC, respectively. Further analysis of the relevant exposure/dose scenarios and consensus of stakeholders with a multi-disciplinary perspective will enable the development of a revised standard, practical from a compliance perspective and protective of all persons.

Trainer Kit Module for DC Motor Speed Control Using Voice Commands Based on Arduino

Based on the results of observations made by researchers through direct observation of lecturers in the field of electricity, Electrical Engineering Education Study Program, it was found that there is a need for additional trainers as learning media in the electrical machine control course. This study aims to find out how to design a trainer kit design module for DC motor speed control using voice commands by utilizing the Arduino microcontroller. We also learned the results of testing the design of a trainer kit design module for DC motor speed control using voice commands by utilizing the Arduino microcontroller. The research method researchers use is the Research and Development (R&amp;D) method, which aims to develop new products or innovations that benefit. Based on the results of expert validation, it can be concluded that the Arduino Microcontroller-Based Trainer Kit Practical Module obtained a high percentage of media experts at 96%, material experts at 95.5%, and language experts at 80%. These results indicate that this module gets the "Very Eligible" category to be applied to the Electrical Machine Control course.

Research on the Isolated Three‐Port DC‐DC Converter with Resonant Parameter Compensation Capability and Its Performance Optimization

AbstractIn order to eliminate the adverse effects caused by power coupling of the isolated three‐port converter (ITPC), this paper proposes a three‐port resonant converter that uses a switch‐controlled‐capacitor (SCC) and an auxiliary inductor, which has resonant parameter compensation capability (RPC‐ITPC). The topology and operational principle of RPC‐ITPC are discussed in detail. To achieve resonant‐type power decoupling, it is usually necessary to ensure that the resonant frequency of the decoupling port resonant tank is consistent with the switching frequency, which puts high demands on the accuracy of the resonant components. To address the sensitivity of resonant‐type power decoupling to the parameters of resonant components, an SCC was adopted to solve the problem. The use of SCC enables the RPC‐ITPC to have resonant parameter compensation capability. In order to further optimize the performance of the RPC‐ITPC, a triple‐phase‐shift (TPS) modulation strategy is proposed to achieve the minimum RMS value of resonant current (MRMS‐TPSMS). Under the MRMS‐TPSMS, the switching devices of the power decoupling port have difficulty achieving ZVS turn‐on. To circumvent this problem, we realize ZVS of the decoupling port switching devices via auxiliary inductor current injection. Finally, a 1 kW experimental prototype was constructed to validate the theoretical propositions presented in this study. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Assessing Learning in Mathematical Sensemaking Electromagnetism Instructions among Rwanda Polytechnic Students at Huye College

In the realm of electromagnetic (EM) courses in engineering, many studies have reported students’ learning difficulties related to mathematical frameworks representing physical phenomena. Students’ learning engagement and learning gains are not satisfying. The present study assessed first-year engineering students’ behavioural engagement and perceived learning gains in mathematical sensemaking electromagnetism instructions at RP-Huye College. Within a single-case research design, a six-weeks intervention incorporating mathematical sensemaking instructions, supported by physical experimentation and computer simulations, was implemented to 61 first-year engineering students who were enrolled in the department of electrical and electronics engineering. All enrolled students were purposively recruited to participate because this target population was less than 100. Data were collected through classroom observations, which used the behavioural engagement related to instruction (BERI) and a post-topic evaluation, which used a semi-structured questionnaire. Data analysis involved the use of graphs, descriptive statistics and inductive thematic analysis. Findings revealed that students were mostly engaged during mathematical sensemaking by hands-on and simulation-based activities, particularly in topics related to electromagnets, where engagement levels peaked at 7.5 in average. Conversely, lecture-based tasks, especially on magnetic forces and electromagnetic induction, recorded the lowest engagement at 6.2 in average. The post-topic assessment on perceived learning gains showed that students had highly positive perceptions on their learning experiences (M=4.82, SD=0.48) and recognized the significance of EM in engineering (M=4.85, SD=0.38). These numerical results were complemented by students’ narrations, which indicated that they gained particular attention about specific EM formulas and how they can apply them in engineering. However, the present study also noted that further refinement in instructional design, particularly by incorporating specific dimensions of mathematical sensemaking, could optimize learning outcomes for EM courses in engineering. Additionally, formal assessments of students’ mastery and experimental studies can benefit future work.