Electronics

Agile Product Line Engineering (APLE), a relatively new approach combining the two successful methods of Agile Software Development (ASD) and Software Product Lines (SPLs), makes product lines more responsive to ever-changing customer needs or market changes. However, SPLs often fail to keep up with market demand due to high coordination costs, slow development processes, and long release cycles in the case of frequent changes in business requirements; in agile software projects, the lack of a unified specification for describing requirements leads to high coordination costs and inconvenient requirement management. Some studies in the literature have proposed optimized approaches to integrate ASD and SPLs, but they still have not covered all aspects of APLE’s characteristics, and software resource reuse is rarely considered in these approaches during product line development. In view of this, we propose a collaborative framework of agile product line engineering for software resource reuse, namely ScrumOntoSPL. The ScrumOntoSPL approach efficiently merges ASD and SPL based on the agile method Scrum, SPL architecture, and ontology technology. In ScrumOntoSPL, uniform requirement specification is constructed by utilizing ontology, and the Matching Requirement with Component (MRC) process is designed to match product new requirements and software resources stored in a resource pool. In addition, we evaluated the proposed framework and approach with CMMI. In the end, a case study of a software development tool called IMC-Tool based on ScrumOntoSPL for a universal Instrument Microcontroller Chip (IMC) is discussed. The IMC-Tool case illustrates that the ScrumOntoSPL has the advantages of dynamically managing demand changes, enhancing software resource reuse, reducing coordination costs, and reducing time to market. Full article

Echo-doppler examination of the jugular vessel is a powerful tool for the early diagnosis of cardiovascular disorders that can be further related to central nervous system diseases. Unfortunately, the ultrasound technique is strongly operator-dependent, so the quality of the scan, the accuracy of the measurement, and therefore the rapidity and robustness of the diagnosis reflect the degree of training. The paper presents the development of a mechatronic simulation system for improving the skill of novice physicians in echo-doppler procedures. The patient is simulated by a silicone manikin whose materials are designed to have a realistic ultrasound response. Two tubes allow blood-mimicking fluid to flow inside the manikin, simulating the hemodynamics of the internal jugular vein. The mechatronic system is designed for controlling the flow waveform, to reproduce several clinical cases of interest for diagnosis. The experiments investigate the accuracy of the echo-doppler measurements performed on the proposed system by novice operators using a real ultrasound scanner. Full article

In industrial applications, it is necessary to select different types of networks according to different communication requirements. To meet this requirement, a converged network of wired and wireless networks is frequently employed. Notably, fulfilling the end-to-end transmission requirements of converged networks is challenging. As a solution, converged-network scheduling methods have proved valuable. In this paper, a network scheduling method for the convergence of industrial wireless networks and time-sensitive networks is proposed. Additionally, the proposed method is tested and verified. The results show that the end-to-end average transmission delay is reduced and the jitter is acceptable. Full article

With the development of power-electronics technology, PWM rectifiers are widely used in many fields. They are especially suitable for high-precision- and high-efficiency-application scenarios, such as communication and industrial control. Although it has many advantages, overshoot control during startup is a challenge. Therefore, this paper first derives the input–output mathematical model through equation establishment and dq-coordinate transformation. Next, a voltage and current double closed-loop simulation model is established in MATLAB/Simulink, and its control effect is analyzed. On this basis, a new voltage-setting strategy is designed to reduce the output-voltage overshoot of the PWM rectifier when starting. The simulation results demonstrate that the strategy has a good application effect and can contain starting-voltage overshooting from 12.88% to 0.925%. Moreover, the principle of this strategy is simpler and easier to understand and implement compared with traditional strategies. Full article

The emotional well-being of a child is crucial for their successful integration into society as a productive individual. While technology has made significant strides in enabling machines to decipher human emotional signals, current research in emotion recognition primarily prioritizes adults, disregarding the fact that children develop emotional awareness at an early stage. This highlights the need to explore how machines can recognize facial expressions in children, although the absence of a standardized database poses a challenge. In this study, we propose a system that employs Convolutional-Neural-Network (CNN)-based models, such as VGG19, VGG16, and Resnet50, as feature extractors, and Support Vector Machine (SVM) and Decision Tree (DT) for classification, to automatically recognize children’s expressions using a video dataset, namely Children’s Spontaneous Facial Expressions (LIRIS-CSE). Our system is evaluated through various experimental setups, including 80–20% split, K-Fold Cross-Validation (K-Fold CV), and leave one out cross-validation (LOOCV), for both image-based and video-based classification. Remarkably, our research achieves a promising classification accuracy of 99% for image-based classification, utilizing features from all three networks with SVM using 80–20% split and K-Fold CV. For video-based classification, we achieve 94% accuracy using features from VGG19 with SVM using LOOCV. These results surpass the performance of the original work, which reported an average image-based classification accuracy of 75% on their LIRIS-CSE dataset. The favorable outcomes obtained from our research can pave the way for the practical application of our proposed emotion recognition methodology in real-world scenarios. Full article

Electric vehicles and the charging stations and their operation require a thorough examination to evaluate the effects on the electrical network. This becomes particularly challenging in the case of high photovoltaic penetration, due to the variability of the solar resource and vehicle connection patterns, which cater to individual user preferences. The current study investigates the impact of harmonics generated by charging stations and electric vehicles on different photovoltaic penetration scenarios within an electrical distribution system. DC and AC charging stations are analyzed. The findings reveal a third harmonic magnitude increase exceeding 300% compared to other cases. Furthermore, this study demonstrates the effects of current and voltage variations on end-users and substation transformers. The impact of harmonics on the hosting capacity of the network is also analyzed, resulting in a 37.5% reduction in the number of vehicles. Full article

The transformation of technological orientation and crowdfunding as innovative concepts combined with cutting-edge digital tools provides the foundation for outstanding fundraising success. Therefore, this study aims to explore the relationship between technology orientation (TO) and crowdfunding performance. Additionally, this research also investigates how crowdfunding digital platform mediates and innovation strategy moderates in the linkage between crowdfunding performance and technology orientation. Data were collected through a questionnaire on the basis of cross-sectional research design. Structural econometric models for direct and indirect analyses were conducted to test hypotheses. The results confirmed the direct positive impact of technology orientation on crowdfunding performance. Moreover, the findings prove the mediating role of a crowdfunding digital platform and moderating role of innovation strategy between technology orientation and crowdfunding performance. Fundraisers are required to give attention to technology orientation for the acceptance and adoption of the latest advancements in technology. They must consider digital platforms for fundraising and pay proper attention to innovation strategy for achieving the needed crowdfunding performance. This research discusses how return base crowdfunding performance occurs; in future, other researchers may provide evidence on donations/charity campaign base crowdfunding. This is the first study in the context of digital transformation that explored the nexus of technology orientation, crowdfunding digital platform and innovation strategy for attaining crowdfunding performance. Full article

Due to sensor characteristics, geographical environment, electromagnetic interference, electromagnetic silence, information countermeasures, and other reasons, there may be significant system errors in sensors in multi-sensor tracking systems, resulting in poor track-to-track association (TTTA) effect of the system. In order to solve the problem of TTTA under large system errors, this paper proposes an asynchronous anti-bias TTTA algorithm that utilizes the average distance between the nearest neighbor intervals between tracks. This algorithm proposes a systematic error interval processing method to track coordinates, and then defines the nearest neighbor interval average distance between interval coordinate datasets and interval coordinate points, and then uses grey theory to calculate the correlation degree between tracks. Finally, the Jonker–Volgenant algorithm is combined to use the canonical allocation method for TTTA judgment. The algorithm requires less prior information and does not require error registration. The simulation results show that the algorithm can ensure a high average correct association rate (over 98%) of asynchronous unequal rate tracks under large system errors, and achieve stable association, with good association and anti-bias performance. Compared with other algorithms, the algorithm maintains good performance for different target numbers and processing cycles, and has good superiority and robustness. Full article

Multi-bit phase shifters are typically implemented by cascading multiple phase-shifting units, therefore incurring large dimensions and higher insertion losses. This paper presents highly compact single-unit two-bit reflection-type phase shifters (SUTBRTPSs), with large phase shifts range and lower insertion loss by using only one 3-dB hybrid coupler, unlike traditional multi-bit reflection-type phase shifters. To achieve this, two identical dual-voltage controlled reactance blocks (DVCRBs) are loaded to the 3-dB hybrid directional coupler at through and coupled ports, and 04 states of phase shifts are obtained between the input and isolated ports. Each DVCRB consists of 03 open-circuited transmission lines and switching p-i-n diodes and provides half of the required susceptance to achieve the desired phase shifts. Design theory is presented in detail, and for validation and demonstration, two typical SUTBRTPSs (0°/45°/90°/135° and 0°/22.5°/180°/202.5°) are designed, fabricated and measured. Being implemented in a single-unit structure, the proposed method yields highly compact dimensions of 0.44 λg × 0.46 λg and 0.54 λg × 0.46 λg, respectively. The simulation and measurements results are in good agreement and indicate maximum insertion losses of 1.7 and 2.1 dB with a return loss better than 20 dB and phase error of less than 1.5°. Full article

Cluster tools are the key equipment in semiconductor manufacturing systems. They have been widely adopted for many wafer fabrication processes, such as chemical and physical vapor deposition processes. Reentrant wafer flows are commonly seen in cluster tool operations for deposition processes. It is very complicated to schedule cluster tools with reentrant processes. For a dual-arm cluster tool with two-time reentering, the existing studies point out that a one-wafer periodical (1-WP) schedule can be found, and it is optimal in terms of productivity. However, for some wafer fabrication processes, wafers should be processed at some PMs more than two times. This gives rise to a question of whether there still exists a 1-WP schedule for dual-arm cluster tools with the number of reentering times being more than two such that the cycle time of a tool can reach the lower bound. This problem is still open, and this is what this work wants to tackle. For a dual-arm cluster tool with the number of reentering times being k (>2) times, if there does not exist a value f ∈ {1, 2 …} such that k = 3f, theoretical proofs are given to show that a 1-WP schedule can be found, otherwise it does not exist. For cases with a 1-WP schedule, the cycle time can be obtained by analytical expressions. For the cases without a 1-WP schedule, two new methods for a three-wafer periodical schedule are proposed to improve the system productivity by comparing it with an existing three-wafer periodical schedule. The applications of the obtained results are demonstrated by examples. Wafer residency time constraints are required for some wafer fabrication processes. Note that the results obtained in this work cannot be directly applied to cluster tools with both reentrant wafer flows and wafer residency time constraints. Nevertheless, schedulablity and scheduling analyses for that applications can be conducted based on the obtained results in this work. Full article

Private set intersection (PSI) is a valuable technique with various practical applications, including secure matching of communication packets in the Internet of Things. However, most of the currently available two-party PSI protocols are based on the oblivious transfer (OT) protocol, which is computationally expensive and results in significant communication overhead. In this paper, we propose a new coding method to design a two-party PSI protocol under the semi-honest model. We analyze possible malicious attacks and then develop a PSI protocol under the malicious model using the Paillier cryptosystem, cut-and-choose, zero-knowledge proof, and other cryptographic tools. By adopting the real/ideal model paradigm, we prove the protocol’s security under the malicious model, which is more efficient compared to the existing related schemes. Full article

Open government data, as open data, are published to let interested stakeholders exploit data and create value out of them, but limited technical skills are a crucial barrier. Moreover, data silos within any public agency behave as a further obstacle in enabling collaboration between different working groups. This paper investigates the acceptance level of a collaborative platform to co-create, analyze, and visualize open government data within an Italian Regional Public Administration—the Campania region. This investigation first requires retracing and documenting the organizational changes applied to the Campania Region in moving from a siloed structure to a more horizontal and collaborative one. Second, it introduces the technical and technological contribution provided by the proposal of a Social Platform on Open Data (SPOD) as a regional public administration back-office, i.e., an internal platform, co-designed with public agency delegates and referred to as Campania Crea. Finally, it reports on the training session moderated by the University of Salerno to evaluate the acceptance rate of the proposed platform in real settings by involving 54 public agency members in actively using Campania Crea to co-create, analyze, and visualize open government data. The After Scenario Questionnaire was used to assess the acceptance level and attitude in using Campania Crea to report task-based results and the Technology Acceptance Model as an overall assessment of the platform acceptance level. As a result, Campania Crea supports regional public administration members in accomplishing their daily tasks concerning co-creation, analysis, and visualization of open data who positively accepted Campania Crea as a back-office tool. However, further effort should be invested in raising awareness and developing skills concerning open government data management. Full article

Aiming at the problems of data loss and uneven energy consumption in wireless sensor networks during data transmission, this paper proposes a ReInForM transmission fault-tolerant routing algorithm based on energy selection and erasure code fault-tolerant machines (E-ReInForMIF). The E-ReInForMIF algorithm improves the multi-path routing algorithm by combining an erasure coding fault-tolerant machine and node residual energy sorting selection. First, the erasure coding fault-tolerant machine is used to encode the signal, determine the number of transmission paths through multi-path routing, and then select the specific node of the next hop by sorting the residual energy of the node. The E-ReInForMIF routing algorithm effectively solves the problems of uneven energy consumption and data loss in data transmission, improving network lifespan and transmission reliability. Finally, the signal is decoded. The simulation results show that the E-ReInForMIF routing algorithm is superior to the ReInForM routing algorithm in improving the reliability of data transmission. Full article

As a critical indicator for assessing the survivability and condition of transformers in a fleet, the transformer health index has attracted attention from both asset owners and international organizations like CIGRE and IEEE DEIS/PES. To provide a systematic and comprehensive review for further study or to guide transformer asset management, this paper summarizes the state-of-the-art of the transformer health index, from the early proposed weighted-score-sum approaches to the more recently proposed artificial intelligence algorithm-based methods. Firstly, different methods for determining the transformer health index are reviewed. Each of these is specified as belonging to a certain type on the basis of its formulation and composition schematic. Subsequently, the steps to determine each type of health index are summarized, and examples derived from literature are provided for further illustration. Comparisons are finally carried out in order to better understand the pros and cons of different types of transformer health index, and the future development trends for transformer health indexes are also discussed. This work can serve as a valuable reference for the survivability and condition assessment of transformers in the power industry. Full article

This research migrates a monolithic smart intercom system to a microservice architecture, making the system more secure, stable, and scalable. The security mechanisms of the instant messaging platform are combined with microservices to improve the security of the system. The stability and performance of microservices are shown to be better than those of monolithic services through experimental tests. Residents can use different instant messaging software instead of the handset to improve the convenience of using this system. This system also implements community broadcasts, platform broadcasts, unit broadcasts, and family broadcasts to exchange messages across different instant messaging platforms. This paper proposes OpenAPI for other smart intercoms to integrate this system’s services and resources. In addition, this study deploys two microservice architectures using a native load balancer with a kube proxy and a service mesh load balancer with an istio proxy. Experiments were conducted during which residents tested the kube proxy and the istio proxy using stress testing tools on two microservice architectures, and the results showed that the kube proxy was slightly better than the istio proxy. Full article

The transformer health index (HI) concept has been used as an important part of management resources and is implemented for the state assessment and ranking of Power transformers. The HI state is estimated based on many power transformer oil parameters. However, the main problem in the HI procedure as a diagnostic method is the presence of routine measurements and accurate test results. The power transformer HI prediction is carried out in this work using 1361 dataset samples collected from two different utilities. The proposed model is used to predict and diagnose the HI state of the power transformer by using a convolutional neural network (CNN) approach. The imbalance between the training dataset sample classes produces a good prediction of the class with a major number of samples while a low detection of the class has a minor number of samples. The oversampling approach is used to balance the training samples to enhance the prediction accuracy of the classification methods. The proposed CNN model predicts the HI of the power transformers after applying the oversampling approach to the training dataset samples. The results obtained with the proposed CNN model are compared with those obtained with the optimized machine learning (ML) classification methods with the superiority of the CNN results. Feature reductions are applied to minimize testing time, effort, and costs. Finally, the proposed CNN model is checked with uncertain noise in full and reduced features of up to ±25% with a good prediction diagnosis of the power transformer HI. Full article

The distributed Goppa-coded generalized spatial modulation (DGC-GSM) scheme with the source, relay, and destination in cooperative communications is proposed, where the source and relay adopt different Goppa codes. Goppa codes have many advantages such as the flexible codeword length, excellent code construction, and easy encoding and decoding complexity. At the relay, we select portions of the source information bits for further encoding. For each selection, the destination constructs a channel code. To obtain the best code in the destination, we propose the optimal information bit selection algorithm at the relay to choose the source information. However, Goppa codes with a large block length will impose high complexity on the optimal algorithm. Thus, the locally optimized selection algorithm is further proposed. At the destination, the joint decoding algorithm is adopted to recover the source information. Our simulated results indicate that the two selection algorithms proposed achieve better performance than the random selection method. This is because the optimized algorithms can generate the code with a larger minimum distance at the destination. Moreover, the proposed DGC-GSM scheme outperforms the non-cooperative system. Moreover, the DGC-GSM scheme can obtain the approximate performance with the distributed Goppa-coded spatial modulation (DGC-SM) scheme but has a significantly reduced transmit antenna number. Full article

In this study, a robot was created to compete in the “7th Decommissioning Creative Robot Contest. The “Decommissioning Creative Robot Contest” is a robot contest in which the fields and tasks are set based on the assumption of decommissioning work at TEPCO’s Fukushima Daiichi Nuclear Power Station. The theme of this year’s competition is 3D decontamination of a highly contaminated area inside a nuclear reactor building. To solve the competition problem, we propose a robot for decommissioning work equipped with “an undercarriage mechanism that can cope with slopes and steps”, “a decontamination mechanism with two types of rotation trajectories”, and “a lifting mechanism with a high deformation rate. The undercarriage mechanism uses a four-wheel drive with infinite orbit to cope with slopes and steps. The decontamination mechanism uses two different types of orbits for decontamination: a circular rotating orbit and a longitudinal rotating orbit for rotation. For the lifting mechanism, three pantograph mechanisms were used. This study realized a control and mechanism to overcome steps and slopes, a deployment mechanism to high places, and a mechanism with two types of orbits to carefully decontaminate a large area. Full article