Search Results (1,124)

Electricity price spikes are the most important characteristic of the electricity price time series. Operationally, they result from various stresses in the power system or the strategic bidding behavior of market participants. These high prices are important as they represent economic opportunities in the form of profits and savings. Theoretically, price spikes are defined as prices that exceed a threshold over a typically short duration. This definition serves as the basis for several established modeling approaches in the literature. In general, the threshold component determines the design of a price spike model, often overlooking the duration aspect. Therefore, this paper presents a simple yet informative model to quantify the duration of electricity price spikes using historical price data from different market jurisdictions. We approach the problem through the lens of survival analysis, a widely used technique for evaluating time-to-event data. Specifically, we use the Kaplan–Meier (KM) estimator, which enables a nonparametric evaluation of the survival (duration) of price spikes over time. We refer to this as the price spike duration model. Full article

Thermal cycling test is one of the reliability tests, which are important for metal-ceramic layered composites (metallized ceramic substrates), a part in power modules. Since thermal cycles are within a large range of temperature, the test has only been performed using a thermal chamber. It limited the understanding of degradation mechanism in metallized ceramics substrates. Among NDE techniques, Digital Image Correlation (DIC) is a simple and effective method, enhanced by modern digital imaging technologies, enabling precise measurements of displacement, strain, deformation, and defects with a simple setup. In this paper, we combined some of our previous work to make a review to present a full analysis of a silicon metallized substrate under thermal cycling test (from beginning to fail) using DIC method. The main content is the application of DIC in evaluating the reliability of metallized silicon nitride (AMB-SN) substrates under thermal cycling with temperatures from −40 °C to 250 °C. Three key aspects of the AMB-SN substrate are presented, including (i) thermal strain characteristics before and after delamination, (ii) warpage and dynamic bending behavior across damage states, and (iii) stress–strain behavior of constituent materials. The review provides insights into degradation progress of the substrate and the role of Cu in substrate failure, and highlights DIC’s potential in ceramic composites, offering a promising approach for improving reliability test simulations and advancing digital transformation in substrate evaluation, ultimately contributing to enhanced durability in high-power applications. Full article

The International Maritime Organization (IMO) has announced regulations that affect many shipbuilding industries and related companies. They require building companies to demonstrate strict compliance with these regulations in construction activities going forward. In response, shipbuilding companies are testing various electrification methods, with the ultimate aim of making ships more eco-friendly. In large ships, in particular, constructors often take a gradual route by hybridizing the propulsion system. In many large cargo ships, the adoption of energy storage systems (ESSs) is expected as part of this transition. In practice, the most frequently operating units inside the ship are the generator engines (GEs). Therefore, this study targets the fluctuation rate characteristics of GEs, providing a more realistic basis for ESS sizing. By focusing on smoothing the GE output, this study determines the ESS capacity required to maintain system stability using a simple moving average (SMA) method and evaluates the fluctuation rate of the GEs under various load conditions. Full article

Speaker verification (SV) is a core technology for security and personalized services, and its importance has been growing with the spread of wearables such as smartwatches, earbuds, and AR/VR headsets, where privacy-preserving on-device operation under limited compute and power budgets is required. Recently, self-supervised learning (SSL) models such as WavLM and wav2vec 2.0 have been widely adopted as front ends that provide multi-layer speech representations without labeled data. Lower layers contain fine-grained acoustic information, whereas higher layers capture phonetic and contextual features. However, conventional SV systems typically use only the final layer or a single-step temporal attention over a simple weighted sum of layers, implicitly assuming that frame importance is shared across layers and thus failing to fully exploit the hierarchical diversity of SSL embeddings. We argue that frame relevance is layer dependent, as the frames most critical for speaker identity differ across layers. To address this, we propose Masked Multi-layer Feature Aggregation (MMFA), which first applies independent frame-wise attention within each layer, then performs learnable layer-wise weighting to suppress irrelevant frames such as silence and noise while effectively combining complementary information across layers. On VoxCeleb1, MMFA achieves consistent improvements over strong baselines in both EER and minDCF, and attention-map analysis confirms distinct selection patterns across layers, validating MMFA as a robust SV approach even in short-utterance and noisy conditions. Full article

In this article, we propose a goodness-of-fit test for a one-parameter Lindley distribution based on energy statistics. The Lindley distribution has been widely used in reliability studies and survival analysis, especially in applied sciences. The proposed test procedure is simple and more powerful against general alternatives. Under different settings, Monte Carlo simulations show that the proposed test is able to be well controlled for any given nominal levels. In terms of power, the proposed test outperforms other existing similar methods in different settings. We then apply the proposed test to real-life datasets to demonstrate its competitiveness and usefulness. Full article

The scaling of microwave plasma technologies from successful laboratory demonstrations to larger industrial applications usually involves an increase in microwave power. This upgrade is accompanied by a higher electron density (and electric conductivity) of the plasma that often limits the power efficiency of the device. In this paper, we address this issue through a focused computational study of electromagnetic characteristics of a microwave system containing plasma. Our approach employs finite-different time-domain analysis supported by a simple model which characterizes the plasma medium using plasma frequency and the frequency of electron-neutral collisions. Based on experimental data for electron density with respect to power, the plasma frequency is generated as a linear function of power, thus enabling a direct understanding of how frequency characteristics of the reflection coefficient and patterns of the electric field may vary for different power levels in a variety of plasma scenarios. For a cavity modeled after conventional plasma applicators, computational results illustrate complex behavior of the field with respect to power. When the power is increased, energy efficiency may decrease, remain low, or increase depending on where the operating frequency stands with respect to the system’s resonances. The proposed modeling approach identifies the system parameters which are most impactful in tuning the system to resonance, thus informing the design variables for subsequent computer-aided design of the scaled system. Full article

Background: This study aims to systematically evaluate the genetic divergence among 200 fresh maize inbred lines using both phenotypic and molecular markers, and to compare the efficacy of these two approaches for genetic classification. Methods: Phenotypic clustering analysis was conducted based on eight key agronomic traits, including plant height and ear length. Additionally, molecular analysis was performed using 40 Simple Sequence Repeat (SSR) primer pairs, resulting in the generation of 230 polymorphic alleles. The polymorphism information content (PIC) was calculated to evaluate the discriminatory power of the markers. Results: Phenotypic analysis categorized the inbred lines into four groups, comprising 25, 38, 97, and 40 lines, respectively, with benchmark lines distributed across Groups I and III. SSR analysis revealed a high level of genetic diversity, with an average of 5.75 alleles per locus and a mean polymorphic information content (PIC) of 0.70. Molecular grouping further divided the population into four distinct clusters, representing 26.5%, 51.0%, 14.0%, and 8.5% of the total, which exhibited different distribution patterns compared to the phenotypic grouping. The distribution of benchmark lines across various molecular groups confirmed their genetic divergence. Conclusions: SSR-based clustering demonstrated superior robustness and reliability compared to phenotypic grouping for genetic discrimination. These findings confirm the substantial genetic diversity present in fresh maize inbred lines and support the preferential use of SSR markers in maize breeding programs for precise genetic characterization. Full article

This paper presents an analytical framework for the channel capacity evaluation of simultaneous wireless information and power transfer (SWIPT)-enabled opportunistic amplify-and-forward (OAF) relaying systems over Rayleigh fading channels. For the SWIPT, we employ a power splitter (PS) at the relay, which splits the received signal into the information transmission and the energy-harvesting parts. By modeling the partial channel state information (P-CSI)-based SWIPT OAF system as an equivalent non-SWIPT OAF configuration, a semi-lower bound and a new upper bound on the ergodic channel capacity are derived. A refined approximation is then obtained by averaging these bounds, yielding a simple yet accurate analytical estimate of the true capacity. Simulation results confirm that the proposed approximations closely track the actual performance across a wide range of signal-to-noise ratios (SNRs) and relay configurations. They further demonstrate that SR-based relay selection provides higher capacity than RD-based selection, primarily due to its direct influence on energy harvesting efficiency at the relay. In addition, diversity advantages manifest mainly as SNR improvements, rather than as gains in diversity order. The proposed framework thus serves as a practical and insightful tool for the capacity analysis and design of SWIPT-enabled cooperative networks, with direct relevance to energy-constrained Internet of Things (IoT) and wireless sensor applications. Full article

Augmented reality (AR)-based assisted maintenance methods are effective in completing simple equipment maintenance tasks. However, complex equipment typically requires multi-location remote collaboration due to structural complexity, multiple fault states, and high maintenance costs, significantly increasing maintenance difficulty. This paper therefore proposes a remote maintenance support method for complex equipment based on layered-MVC-B/S integrated AR framework (IAR-RMS). First, clearly define the maintenance content and workflow for multi-person remote collaboration and conduct an in-depth analysis of process control within the task workflow to avoid incomplete or unsystematic maintenance guidance information and processes. Second, analyze collaborative management from the perspectives of maintenance role conflicts and maintenance operation conflicts and implement on-demand permission control and operation sequence management to ensure the timeliness and user-friendliness of multi-person collaboration. Then, integrate the layered architecture, MVC, and B/S architecture to construct a remote maintenance support (RMS) model based on an integrated architecture system, ensuring the reliability and timeliness of the model. Finally, demonstrate the main functional modules of the RMS task process, and use power system disassembly and assembly as an experiment to validate the effectiveness and generalizability of the proposed IAR-RMS method. The results indicate that the proposed IAR-RMS method can effectively realize maintenance support tasks in multi-person remote collaboration scenarios. Full article

This paper presents a new compact and efficient first-order all-pass filter in voltage mode based on a second-generation voltage conveyor, along with two resistors, and a capacitor. This circuit delivers an all-pass response from the low-impedance node and eliminates the need for a voltage buffer in cascading configurations. A thorough non-ideal analysis, accounting for parasitic impedances and the non-ideal gains of the active module, shows negligible effects on the filter performance. Furthermore, a sensitivity analysis with respect to both active and passive components further validates the robustness of the design. The proposed all-pass filter is validated by Cadence PSPICE simulations, utilizing 0.18 µm TSMC CMOS process parameter and ±0.9 V power supply, including Monte Carlo analysis and temperature variations. Additionally, experimental validation is carried out using commercially available IC AD844, showing great consistency between theoretical and experimental results. Resistor-less realization of the proposed filter provides tunability feature. A quadrature sinusoidal oscillator is presented to validate the proposed structure. The introduced circuit provides a simple and effective solution for low-power and compact analog signal processing applications. Full article

Background/Objectives: The diagnosis of melanocytic lesions on the trunk is challenging due to a high frequency of atypical features in benign nevi, leading to a high rate of unnecessary excisions. This study aimed to identify robust dermoscopic predictors of cutaneous melanoma on the trunk and to evaluate a novel diagnostic criterion: the orientation of lesions relative to Langer’s skin tension lines. Methods: We conducted a retrospective analysis of 321 melanocytic lesions (227 nevi and 94 melanomas) excised from the trunk. Dermoscopic features were systematically evaluated. A chi-square test and an age- and sex-adjusted multivariate logistic regression were performed to calculate odds ratios (OR) and identify independent predictors of malignancy. A subgroup analysis was also conducted on “critical” versus “non-critical” anatomical sites. Results: Non-adherence to Langer’s lines was the most powerful predictor of melanoma (OR 5.55, 95% CI 3.22–9.81; p < 0.001). Other significant predictors included blue-white veil (OR 5.09) and polymorphous vessels (OR 4.06). Notably, 70% of melanomas did not align with Langer’s lines, whereas 72% of nevi did. Classic features such as scar-like regression were not statistically significant predictors in this cohort. In the subgroup analysis, color asymmetry was a significant predictor of melanoma only in non-critical sites (p for interaction = 0.026). Conclusions: The orientation of a melanocytic lesion relative to Langer’s lines is a powerful and independent predictor of melanoma on the trunk. This simple morphological feature, which may reflect differences in growth patterns between malignant and benign lesions, could serve as an additional clinical cue to support decision-making and improve diagnostic accuracy in this challenging anatomical location. Full article

Background: This study aims to examine the relationship between Kinesiophobia and Rumination in athletes, and to reveal the mediating roles of Coping Responses and Psychological Flexibility in this relationship. Methods: Three hundred ninety licensed athletes, including 225 females and 165 males, voluntarily participated in the study. Participants were selected through simple random sampling from various sports clubs across Turkey. During the data collection, participants were contacted online. They completed the personal ınformation form, the Tampa Scale of Kinesiophobia, the Sport Competition Rumination Scale, the Psychological Flexibility Scale, and the Coping Responses Inventory. IBM SPSS 26 and PROCESS Macro Model 4.0 were used for data analysis. In addition to descriptive statistics, Pearson correlation, linear regression, and mediation analyses were conducted. The adequacy of the sample size was evaluated using G*Power (v 3.1). The Bootstrap method with 5000 resamples and a 95% confidence interval was applied in the mediation analysis. Results: The study’s findings indicated that kinesiophobia significantly predicted levels of rumination among athletes, and that both psychological flexibility and coping responses partially mediated this relationship. Although both variables were functional in reducing ruminative thinking, coping responses demonstrated a more potent effect. The results suggest that the tendency to avoid movement affects physical and cognitive processes. Conclusions: It was concluded that psychological flexibility and coping responses are protective factors in reducing repetitive negative thought patterns in athletes. In this regard, it is recommended that holistic intervention programs aimed at enhancing psychological resilience be developed to support mental health and athletic performance. Full article

This paper presents the design, implementation, and experimental results of a six-degree-of-freedom Delta-type parallel manipulator, in which all actuators were realized using proprietary pneumatic muscles. The objective of the study was to evaluate the suitability of this type of actuator for applications in parallel robotics, with particular attention to their dynamic properties, nonlinearities, and potential limitations. In the first part of the article, the details of the manipulator’s construction and the kinematic model, covering both the forward and inverse kinematics, are presented. The control system was based on antagonistic pairs of pneumatic muscles forming servo drives responsible for the motion of individual arms. The experimental investigations were focused on analyzing trajectory-tracking accuracy and positioning repeatability, both in unloaded conditions and under additional payload applied to the end-effector. The results indicate that positioning errors for simple trajectories were generally below 1 mm, whereas for complex trajectories and under load, they increased, particularly during changes in motion direction, which can be attributed to friction and hysteresis phenomena in the muscles. Repeatability tests confirmed the ability of the manipulator to repeatedly reach the desired positions with small deviations. The analysis carried out confirms that pneumatic muscles can be effectively applied to drive parallel manipulators, offering advantageous features such as high power density and low mass. At the same time, the need for further research on nonlinearity compensation and durability enhancement was demonstrated. Full article

This paper proposes a data-driven framework for user–feeder topology identification in low-voltage residential power networks using ambient (current and voltage) measurements from smart meters. The framework first prepossesses the raw dataset via wavelet-based denoising, principal component analysis-based dimensionality reduction, and deep learning-based temporal feature extraction. In addition, a deep learning-based anomaly detection approach is also applied. Seven clustering algorithms are adopted for user–feeder relationship identification, and then the results are fused via a result-fusion strategy to enhance the identification accuracy further. Experiments on three real-world residential power networks demonstrate that the proposed approach significantly outperforms the results obtained by a single clustering method and the results obtained by simple voting-based fusion. The proposed approach achieves up to 88% identification accuracy in the considered case studies. Ablation studies are also conducted to validate the importance of each module in the proposed framework. Full article

We present a single-slab metasurface that converts a normally incidental linearly polarized wave into either right- or left-handed circular polarization (RHCP/LHCP) through a simple ${90}^{\circ }$ mechanical rotation. Each unit cell comprises two L-shaped metallic resonators placed on the opposite faces of a low-permittivity substrate. Operating in transmission mode, the linear-to-circular (LTC) converter does not require any active electronic components. The geometry is optimized by using full-wave simulations to maximize the conversion up to 26% relative bandwidth with polarization conversion efficiency up to 65%, and insertion loss below 1.3 dB. Power balance analysis confirms low-loss, impedance-matched behavior. A scaled prototype fabricated from AWG-25 steel wires validates the model: experimental measurements closely reproduce the simulated bandwidth and demonstrate robust handedness switching. Because the resonance frequency depends primarily on resonator length and unit-cell pitch and thickness, the design can be retuned across the microwave spectrum through straightforward geometrical scaling. These results suggest that mechanical rotation could provide a simple and reliable alternative to electronic tuning in reconfigurable circular polarizers. Full article