Electronics

When performing weak flux control to drive a permanent-magnet synchronous motor at high speed, the efficiency is lowered because the copper loss increases as the negative D-axis current increases. In addition, if the overmodulation index is slightly lowered and driven without setting it to the maximum value, the phase current ripple reduction effect can be expected compared to the six-step control. Therefore, if the motor is operated at a current point that can minimize the sum of copper loss and iron loss, the motor can be driven with maximum efficiency. In addition, if the overmodulation index is slightly lower than that of the six-step control, the phase current ripple can be reduced. This paper proposes a method for finding an overmodulation index to maximize driving efficiency when driving a motor based on the magnetic flux–torque command. In addition, an algorithm for driving a motor with maximum efficiency by applying an optimal overmodulation index table is proposed. Based on the MATLAB Simulink simulation, the efficiency change characteristics according to the overmodulation index change are reviewed, and the efficiency improvement and current ripple reduction effects are verified through a dynamometer experiment. Full article

Robot trajectory prediction is an essential part of building digital twin systems and ensuring the high-performance navigation of IoT mobile robots. In the study, a novel two-stage multi-objective multi-learner model is proposed for robot trajectory prediction. Five machine learning models are adopted as base learners, including autoregressive moving average, multi-layer perceptron, Elman neural network, deep echo state network, and long short-term memory. A non-dominated sorting genetic algorithm III is applied to automatically combine these base learners, generating an accurate and robust ensemble model. The proposed model is tested on several actual robot trajectory datasets and evaluated by several metrics. Moreover, different existing optimization algorithms are also applied to compare with the proposed model. The results demonstrate that the proposed model can achieve satisfactory accuracy and robustness for different datasets. It is suitable for the accurate prediction of robot trajectory. Full article

The health of aero-engines is pivotal to the safe operation of aircraft. With increasing service time, the internal components of the engine will be damaged by threats from different sources, so it is necessary to regularly detect the damage inside the engine. At present, most of the detection methods of major airlines rely on the internal images of the engine obtained by manual use of a borescope to detect damage or traditional machine learning methods, which consume high levels of human and computational resources but have low efficiency. Artificial intelligence in various fields can achieve better performance than traditional methods, but to achieve the industrialization standard of Green AI, we need further research. Accordingly, we introduce a multi-layer contrastive learning method to a lightweight target detection model design, which is applied to real aero-engine borescope images of complex components to accomplish real-time damage detection. We intensively conduct comparative experiments to evaluate the effectiveness of our method. The verification results demonstrate that the method can help our model perform excellently compared with other available baseline models. Full article

A 6 MeV hybrid photo-cathode gun is driving a THz-FEL in Ariel University, as well as other applications. An electron bunch with small transverse emittance is extracted from a copper photo-cathode using a 1 ps UV laser pulse, and then accelerated to a kinetic energy of 6.5 MeV. The Hybrid term is due to the unique standing wave-traveling wave sections in a single RF cavity. Since low emittance is crucial for FEL operation, the characterization of the electron beam requires measuring the transverse emittance, which will be compared with the predicted design and the 3D simulation obtained values, in order to verify their correctness. In this paper, we confirm the use of the multi-slit technique to measure emittance in the Hybrid beam in a single shot and develop a simple and convenient algorithm to be used in the experimental measurements. The experimental analysis requires image processing of the measured data, combined with a custom LabVIEW and Matlab scripts to control the hardware, and analyze the obtained data. Prior to experimentally measuring emittance, we perform a simulated experiment, using a simulated beam from the General Particle Tracer (GPT) code to test these algorithms and scripts, and compare the emittance obtained using the algorithm with GPT’s estimated emittance. Once concluded, this method will allow for a simple, fast and accurate single shot emittance measurement for the Hybrid accelerator beam. Full article

The performance of WR-3.4 overmoded waveguide modules containing a linear array of discrete terahertz integrated circuits is presented to verify a new power-combining technique. Custom-designed thru-line IC chips that include back-to-back broadband antenna transitions were fabricated with an area of 390 × 750 mm² for waveguide packaging. Multiple array modules were assembled to verify the repeatability in performance. The array modules exhibited almost identical amounts of insertion losses compared with single-element modules, showing the best insertion loss of 2.6 dB over a 1 dB bandwidth of 95 GHz. Full article

Due to the COVID-19 pandemic, the entire process of teaching and learning moved online. This forced teachers and pupils to heavily rely on information and communications technology (ICT) and make adjustments to the new mode of teaching and learning in educational institutions. We conducted a qualitative case study by interviewing 24 teachers from Slovene primary schools focusing on the implementation of cross-curricular connections in music and visual arts content with the support of ICT during the period of emergency remote teaching. We found that when planning and implementing the cross-curricular learning process, teachers insufficiently took advantage of possibilities offered by modern ICT. The manner of implementing cross-curricular connections showed uncertainties in terms of understanding their specifics, resulting in the inefficient transfer of concepts taught, the results of which were seen in pupils’ work. This might additionally show the negative influence of parental supervision on the creative thinking and expression of pupils. The present study emphasizes the lack of ICT competences on the part of all participants in the educational process. Our findings show the need to educate teachers by eliminating the uncertainties related to the implementation of distant cross-curricular connections while meaningfully applying ICT adapted to pupils’ competences. Full article

Both robustness and self-repairing of the rhythmic behaviors generated by central pattern generators (CPGs) play significant roles in locomotion control. Although current CPG models have been established to mimic rhythmic outputs, the mechanisms by which the self-repairing capacities of CPG systems are formed are largely unknown. In this paper, a novel bio-inspired self-repairing CPG model (BiSRP-CPG) is proposed based on the tripartite synapse, which reveals the critical role of astrocytes in the dynamic coordination of CPGs. BiSRP-CPG is implemented on the parallel FPGA platform to simulate CPG systems on real physiological scale, in which a hardware implementation method without multiplier is utilized to break the limitation of FPGA hardware resources. The experimental results verified both the robustness and self-repairing capabilities of rhythm of BiSRP-CPG in the presence of stochastic synaptic inputs and “faulty” synapse. Under the synaptic failure rate of 20%, BiSRP-CPG suffered only 10.53% performance degradation, which was much lower than the 36.84% spike loss rate of CPG networks without astrocytes. This paper provides an insight into one of the possible self-repair mechanisms of brain rhythms which can be utilized to develop autonomously fault-tolerant electronic systems. Full article

A novel integrated multi-winding inductive filter converter and its filter system used in HVDC conversion station are proposed. Specifically, the schemes include two paralleled-connected delta filter windings with zero impedance, and the 11th and 13th tuned filtering branches are installed at the taps. On this basis, the 5th and 7th harmonic filters are eliminated and the 5th, 7th, 11th, and 13th harmonics of the valve-side are suppressed. Moreover, the cost of the filter is reduced, and the negative impact on the converter transformer body caused by the transfer of harmonic current is avoided, such as vibration, noise, and harmonic loss. In this paper, first, the mathematical models of integrated multi-winding inductive filter converter and its filter system are established. Accordingly, the current relationships between the primary winding side and two secondary winding sides are derived. Then, the transfer path of each characteristic harmonic current in the new system is analyzed and discussed. Moreover, a simulation model is established to study the operation characteristics of the system. Finally, through the designed experimental prototype, a new DC transferring system platform is constructed to testify the operation characteristics of an integrated multi-winding inductive filter converter and its filter system. The experimental results show that the total harmonic distortion rate of the grid-winding current can be reduced to 4.68% only by installing the 11th and 13th tuned filters, so the effect of active filtering is approximated realized by the passive filtering method. Full article

Multi-frame X-ray images (videos) of the coronary arteries obtained using coronary angiography (CAG) provide detailed information about the anatomy and blood flow in the coronary arteries and play a pivotal role in diagnosing and treating ischemic heart disease. Deep learning has the potential to quickly and accurately quantify narrowings and blockages of the arteries from CAG videos. A CAG consists of videos acquired separately for the left coronary artery and the right coronary artery (LCA and RCA, respectively). The pathology for LCA and RCA is typically only reported for the entire CAG, and not for the individual videos. However, training of stenosis quantification models is difficult when the RCA and LCA information of the videos are unknown. Here, we present a deep learning-based approach for classifying LCA and RCA in CAG videos. Our approach enables linkage of videos with the reported pathological findings. We manually labeled 3545 and 520 videos (approximately seven videos per CAG) to enable training and testing of the models, respectively. We obtained F1 scores of 0.99 on the test set for LCA and RCA classification LCA and RCA classification on the test set. The classification performance was further investigated with extensive experiments across different model architectures (R(2+1)D, X3D, and MVIT), model input sizes, data augmentations, and the number of videos used for training. Our results showed that CAG videos could be accurately curated using deep learning, which is an essential preprocessing step for a downstream application in diagnostics of coronary artery disease. Full article

Simultaneous localization and mapping (SLAM) is a dual process responsible for the ability of a robotic vehicle to build a map of its surroundings and estimate its position on that map. This paper presents the novel concept of creating a 3D map based on the adaptive Monte-Carlo location (AMCL) and the extended Kalman filter (EKF). This approach is intended for inspection or rescue operations in a closed or isolated area where there is a risk to humans. The proposed solution uses particle filters together with data from on-board sensors to estimate the local position of the robot. Its global position is determined through the Rao–Blackwellized technique. The developed system was implemented on a wheeled mobile robot equipped with a sensing system consisting of a laser scanner (LIDAR) and an inertial measurement unit (IMU), and was tested in the real conditions of an underground mine. One of the contributions of this work is to propose a low-complexity and low-cost solution to real-time 3D-map creation. The conducted experimental trials confirmed that the performance of the three-dimensional mapping was characterized by high accuracy and usefulness for recognition and inspection tasks in an unknown industrial environment. Full article

Vehicular clouds are considered an attractive approach to provide various services such as safety and entertainment applications by sharing resources between vehicles. Due to the free mobility of vehicles, vehicular clouds need to reconstruct by replacing leaving member vehicles with new member vehicles. When multiple member vehicles leave a vehicular cloud at different times, the design of an efficient member vehicle replacement scheme is a very challenging issue on determining the replacement timing. However, the research on the replacement of multiple member vehicles has little interest and is still in its infancy. Therefore, we propose three schemes to replace multiple member vehicles in vehicular clouds at three different replacement timings: MIN, MAX, and AVG. The MIN scheme replaces all of leaving member vehicles at the leaving time of the first leaving member vehicle, while the MAX scheme replaces all of leaving member vehicles at the leaving time of the last leaving member. The AVG scheme replaces all leaving member vehicles at the average time of their leaving times as a compromise between the Min and Max schemes. First, we determine the first leaving time, the last leaving time, and the average leaving time for each scheme by calculating the distance between a cloud requester vehicle and its member vehicles. Next, we choose replacement member vehicles to minimize the wasted resource at the replacement timing in each scheme. Last, we provide the process for releasing the resource of the leaving member vehicles and allocating the resource of the replacement member vehicles in each scheme. Through simulation results conducted in various environments, we compare and evaluate the performance of our three schemes in terms of the success ratio of the cloud maintenance and the amount of the wasted resources. Full article

There are contexts where TCP/IP is not suitable for performing data transmission due to long delays, timeouts, network partitioning, and interruptions. In these scenarios, mobile opportunistic networks (MONs) are a valid option, providing asynchronous transmissions in dynamic topologies. These architectures exploit physical encounters and persistent storage to communicate nodes that lack a continuous end-to-end path. In recent years, many routing algorithms have been based on social interactions. Smartphones and wearables are in vogue, applying social information to optimize paths between nodes. This work proposes Refine Social Broadcast (RSB), a social routing algorithm. RSB uses social behavior and node interests to refine the message broadcast in the network, improving the delivery probability while reducing redundant data duplication. The proposal combines the identification of the most influential nodes to carry the information toward the destination with interest-based routing. To evaluate the performance, RSB is applied to a simulated case of use based on a realistic loneliness detection methodology in elderly adults. The obtained delivery probability, latency, overhead, and hops are compared with the most popular social-based routers, namely, EpSoc, SimBet, and BubbleRap. RSB manifests a successful delivery probability, exceeding the second-best result (SimBet) by 17% and reducing the highest overhead (EpSoc) by 97%. Full article

The vortex electromagnetic wave improves the range-azimuth forward-looking imaging performance with its spiral spatial phase distribution. However, the beam of the vortex electromagnetic wave is divergent, which makes it difficult to detect the targets near the center of the beam. In addition, the vortex electromagnetic wave only has the phase change in the azimuth direction and can hardly estimate the elevation position of the targets. In this paper, a linear wavefront control method based on the amplitude weighting of the array antenna is proposed. The modulated field has a phase gradient in both azimuth and elevation directions and has a maximum radiation intensity in the center of the beam. The imaging model based on the modulated field is theoretically derived and simulations are conducted to demonstrate the imaging performance. The modulated field constructed by the linear array can realize range-azimuth two-dimensional imaging with azimuth resolution of 1/5 beam width. The modulated field constructed by the circular array can realize range-azimuth-elevation three-dimensional imaging, and the resolution of the azimuth and elevation directions is 1/3 of the beam width. Full article

The methodology for constructing intrusion detection systems and improving existing systems is being actively studied in order to detect harmful data within large-capacity network data. The most common approach is to use AI systems to adapt to unanticipated threats and improve system performance. However, most studies aim to improve performance, and performance-oriented systems tend to be composed of black box models, whose internal working is complex. In the field of security control, analysts strive for interpretation and response based on information from given data, system prediction results, and knowledge. Consequently, performance-oriented systems suffer from a lack of interpretability owing to the lack of system prediction results and internal process information. The recent social climate also demands a responsible system rather than a performance-focused one. This research aims to ensure understanding and interpretation by providing interpretability for AI systems in multiple classification environments that can detect various attacks. In particular, the better the performance, the more complex and less transparent the model and the more limited the area that the analyst can understand, the lower the processing efficiency accordingly. The approach provided in this research is an intrusion detection methodology that uses FOS based on SHAP values to evaluate if the prediction result is suspicious and selects the optimal rule from the transparent model to improve the explanation. Full article

Electrowetting display (EWD) is one of the latest and most promising reflective displays. However, some defects are easily caused in a driving process. For example, the aperture ratio of pixels can be reduced due to oil splitting, and the grayscale cannot be stabilized due to charge trapping. These defects can be effectively solved by designing driving waveforms for EWDs. So, a power function driving waveform was proposed in this paper, which consisted of an oil splitting suppression stage, a direct current (DC) driving stage and an oil stabilization stage. Firstly, the relationships among luminance values, power constants and driving time were measured. An optimal oil splitting suppression stage was obtained, which could effectively inhibit oil splitting. Then, the response time could be reduced by a DC voltage in the DC driving stage. Finally, a voltage slope was tested during the oil stabilization stage, which was used to counteract voltage created by the charge trapping. The experimental results showed that compared with a linear function waveform, the response time could be shortened by 16.1%, and the luminance value could be increased by 3.8%. The aperture ratio and oil stability of EWD can be effectively improved by these findings, thereby increasing its potential application in the display field. Full article

The development of devices for the Internet of Things (IoT) requires the rapid prototyping of different hardware configurations. In this paper, a modular hardware platform allowing to prototype, test and even implement IoT appliances on low-cost reconfigurable devices is presented. The proposed platform, named Dracon, includes a Z80-clone microprocessor, up to 64 KB of RAM, and 256 inputs/outputs (I/Os). These I/Os can be used to connect additional co-processors within the same FPGA, external co-processors, communications modules, sensors and actuators. Dracon also includes as default peripherals a UART for programming and accessing the microprocessor, a Real Time Clock, and an Interrupt Timer. The use of an 8-bit microprocessor allows the use of the internal memory of the reconfigurable device as program memory, thereby, enabling the implementation of a complete IoT device within a single low-cost chip. Indeed, results using a Spartan 7 FPGA show that it is possible to implement Dracon with only 1515 6-input LUTs while operating at a maximum frequency of 80 MHz, which results in a better trade-off in terms of area and performance than other less powerful and less versatile alternatives in the literature. Moreover, the presented platform allows the development of embedded software applications independently of the selected FPGA device, enabling rapid prototyping and implementations on devices from different manufacturers. Full article

This paper describes the design of a novel Ku-band slotted waveguide antenna (SWA), taking into consideration the advantages and drawbacks of using a 3D direct metal laser sintering (DMLS) process. Indeed, the DMLS process makes it possible to produce a SWA with 64 radiating slots and its feeding network in a single and monolithic process. However, considering the lack of accuracy of the process, the whole design must be completely thought out and planned to avoid sensitive dimensions. Coupling irises inside such structures are elements of major sensitivity in this regard, so the radiating waveguides in the present work were designed to be TE20 ones, avoiding this kind of iris. Thus, a TE10 to TE20 converter was designed to be implemented in the overall power supply structure of an antenna array made up of four linear SWAs with 16 slots each. Both the elementary 16-slot SWA and the complete SWA with the feeding network were manufactured using DMLS. At a resonant frequency of 15 GHz, the measured realized gain is 22.26 dB with sidelobe levels below 10.1 dB. The measured reflection coefficient is lower than −12.6 dB at the center frequency. These measured performances confirm the proof of concept. Full article

In recent years, various applications have emerged requiring linear topologies of wireless sensor networks (WSN). Such topologies are used in pipeline (water/oil/gas) monitoring systems. The linear structure has a significant impact on network performance in terms of delay, throughput, and power consumption. Regarding communication efficiency, routing protocols play a critical role, considering the special requirements of linear topology and energy resources. Therefore, the challenge is to design effective routing protocols that can address the diverse requirements of the monitoring system. In this paper, we present various wireless communication technologies and existing leak detection systems. We review different routing protocols focusing on multi-hop hierarchical protocols, highlighting the limitations and design issues related to packet routing in linear pipeline leak detection networks. Additionally, we present a LoRa multi-hop model for monitoring aboveground oil pipelines. A set of model parameters are identified such as the distance between sensors. In addition, the paper determines some calculations to estimate traffic congestion and energy consumption. Several alternative model designs are investigated. The model is evaluated using different multi-hop communication scenarios, and we compare the data rate and energy to provide an energy-efficient and low-cost leak detection system. Full article

The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate for a long duration without the presence of a consistent power source. In this paper, we develop a batteryless, ultra-low-power Wireless Sensor Transmission Unit (WSTx) depending on the solar-energy harvester and LoRa technology. We investigate the feasibility of harvesting ambient indoor light using polycrystalline photovoltaic (PV) cells with a maximum power of 1.4 mW. The study provides comprehensive power management design details and a description of the anticipated challenges. The measured power consumption of the developed WSTx was 0.02109 mW during the sleep mode and 11.1 mW during the operation mode. The harvesting system can harvest energy up to 1.2 mW per second, where the harvested energy can power the WSTx for six hours with a maximum power efficiency of 85.714%. Full article