Search Results (92)

Sensor fusion in intelligent suspension systems constitutes a fundamental technology for optimizing vehicle dynamic stability, ride comfort, and occupant safety. By integrating data from multiple sensor modalities, this study proposes a hierarchical multi-sensor fusion framework for active suspension control, aiming to enhance control precision. Initially, a binocular vision system is employed for target detection, enabling the identification of lane curvature initiation points and speed bumps, with real-time distance measurements. Subsequently, the integration of Global Positioning System (GPS) and inertial measurement unit (IMU) data facilitates the extraction of road elevation profiles ahead of the vehicle. A BP-PID control strategy is implemented to formulate mode-switching rules for the active suspension under three distinct road conditions: flat road, curved road, and obstacle road. Additionally, an ant colony optimization algorithm is utilized to fine-tune four suspension parameters. Utilizing the hardware-in-the-loop (HIL) simulation platform, the observed reductions in vertical, pitch, and roll accelerations were 5.37%, 9.63%, and 11.58%, respectively, thereby substantiating the efficacy and robustness of this approach. Full article

High-pitched noise generated by dental air turbine handpieces (ATHs) causes discomfort and anxiety, discouraging dental visits. Understanding the time-dependent noise generation mechanism associated with compressed airflow in ATHs is crucial for effective noise reduction. However, the direct investigation of airflow dynamics within ATHs is challenging. The transient-state modeling of computational fluid dynamics (CFD) simulations remains unexplored owing to the complexities of high rotational speeds and air compressibility. This study develops a novel CFD framework for transient (time-dependent) modeling under high-speed rotational conditions. Simulations were performed using a three-dimensional model reconstructed from a commercial ATH. Simulations were conducted at 320,000 rpm using a novel framework that combines the immersed boundary and building cube methods. A fine 0.025 mm mesh spacing near the ATH, combined with supercomputing resources, enabled the simulation of hundreds of millions of cells. The simulation results were validated using experimental noise measurements. The CFD simulation revealed transient airflow and aeroacoustic behavior inside and around the ATH that closely matched the prominent frequency peaks from the experimental data. This study is the first to simulate the transient airflow of ATHs. The proposed CFD model can accurately predict aeroacoustics, contributing to the future development of quieter and more efficient dental devices. Full article

The growing demand for cost-effective, high-quality protein ingredients in the meat industry highlights the need for advanced processing methods capable of producing uniform, functional meat–bone pastes from poultry by-products. This study investigates the optimization of colloid milling parameters for the fine grinding of chicken meat–bone by-products, with a focus on improving particle size distribution, rheological properties, and processing efficiency. A modified rotor–stator system with teeth inclined at 20° and a reduced pitch (0.5 mm) was compared to a conventional configuration (45° inclination, 1.5 mm pitch). Experiments were conducted at rotor speeds ranging from 1000 to 4000 rpm, with a fixed clearance of 0.1 mm. The results showed that the modified design significantly enhanced grinding efficiency, reducing the proportion of bone fragments > 1 mm and yielding over 70% of particles under 0.1 mm at 3000 rpm. Viscosity and shear stress measurements indicated that grinding at 3000 rpm yielded a dynamic viscosity of 71,507 Pa·s and a shear stress of 43,531 mPa·s, values that were significantly lower (p < 0.05) than those observed at other tested speeds, thereby producing a paste consistency with the most favorable balance of elasticity and flowability. At 4000 rpm, the temperature rise (up to 32 °C) led to partial denaturation of muscle proteins, accompanied by emulsion destabilization and disruption of the protein gel matrix, resulting in reductions in the viscosity and water-binding capacity of the paste. Comparative analysis confirmed that tool geometry and rotor speed have critical effects on grinding quality, energy use, and thermal load. The optimal operating parameters, 3000 rpm with modified rotor–stator teeth, achieve the finest, most homogeneous bone paste while preserving protein functionality and minimizing energy losses. These findings support the development of energy-efficient grinding equipment for the valorization of poultry by-products in emulsified meat formulations. Full article

This systematic review synthesizes 82 peer-reviewed studies published between 2014 and 2024 on the use of audio features in educational research. We define audio features as descriptors extracted from audio recordings of educational interactions, including low-level acoustic signals (e.g., pitch and MFCCs), speaker-based metrics (e.g., talk-time and participant ratios), and linguistic indicators derived from transcriptions. Our analysis contributes to the field in three key ways: (1) it offers targeted mapping of how audio features are extracted, processed, and functionally applied within educational contexts, covering a wide range of use cases from behavior analysis to instructional feedback; (2) it diagnoses recurrent limitations that restrict pedagogical impact, including the scarcity of actionable feedback, low model interpretability, fragmented datasets, and limited attention to privacy; (3) it proposes actionable directions for future research, including the release of standardized, anonymized feature-level datasets, the co-design of feedback systems involving pedagogical experts, and the integration of fine-tuned generative AI to translate complex analytics into accessible, contextualized recommendations for teachers and learners. While current research demonstrates significant technical progress, its educational potential is yet to be translated into real-world educational impact. We argue that unlocking this potential requires shifting from isolated technical achievements to ethically grounded pedagogical implementations. Full article

In this study, a correction procedure for ship mass and its longitudinal location of center of gravity suitable for a simulation environment is proposed in OpenFOAM v6.0. The concept is implemented ensuring static equilibrium and an approximately zero-pitch moment on the ship before the simulation. The viscous flow field around the ship in calm water is simulated using the VOF (Volume of Fluid) free surface two-phase and SST (Shear Stress Transport) k–ω turbulence models. Using static mesh, the resistance error of medium and fine grids is 4%, on average, against the experimental value. As the sinkage and trim are predicted using dynamic mesh, the increasing ship’s resistance causes larger errors, except for the container ship. Through the proposed correction, the ship’s vertical motions are significantly improved, and the resistance error decreases for the dynamic simulation. For the container ship, the error of resistance and motion achieved is less than 1%. The sinkage and trim errors improve tremendously for the tanker and bulk carrier, and the resistance errors are reduced slightly, by less than 3%. In the end, the detailed flow field is analyzed, as well as the ship wave-making pattern and the nominal wake velocity distribution, and these are compared with the measurement data available. The characteristics of the flow phenomena are successfully modeled. The resistance value for each hull form satisfies the requirement of Verification and Validation, and the uncertainty values are estimated. Full article

Mycoviruses are viruses that infect fungi, including plant pathogens. The infection of these mycoviruses is sometimes associated with impaired phenotypes of their fungal hosts, a phenomenon known as hypovirulence. Thus, using mycoviruses as biological control agents has emerged as a promising tool to combat forest diseases. The invasive ascomycete fungus Fusarium circinatum, which causes pine pitch canker (PPC) disease in Pinus tree species and other coniferous trees, is infected by the mycovirus Fusarium circinatum mitovirus 1 (FcMV1), FcMV2-1, and FcMV2-2. However, its impact on pathogen fitness remains unclear. The most accurate method used to identify the effect of a mycovirus on its host is the generation of isogenic lines with and without the mycovirus. The present study aimed to cure F. circinatum isolates infected by FcMV1 using different approaches. For this purpose, three replicates of each isolate were exposed to thermal treatment (38 °C) and antibiotic treatment (ribavirin, cycloheximide, kanamycin, and rifampicin mixed with cAMP)(cyclic adenosine monophosphate) for five successive passages. The viral titer of FcMV1 was then assessed using qPCR (quantitative polymerase chain reaction) after the first week and after the fifth week of the treatment. The results revealed differences in treatment efficacy among F. circinatum isolates, with some showing very low virus titers at the end of the experiment. Both thermal and antibiotic treatment effectively reduced the viral load in all isolates. In addition, the antibiotic cycloheximide and rifampicin +cAMP reduced the viral titer more than ribavirin and kanamycin. The isolate Fc179 was found to be more prone to antibiotic treatment than the other two isolates (001 and Va221). This study demonstrated the possibility of using some isolates of F. circinatum for fine-tuning cures for mitovirus, in order to create virus-free strains for biological control in the future. Full article

Thermal analysis is an indispensable aspect of semiconductor packaging. Excessive operating temperatures in integrated circuit (IC) packages can degrade component performance and even cause failure. Therefore, thermal resistance and thermal characteristics are critical to the performance and reliability of electronic components. Machine learning modeling offers an effective way to predict the thermal performance of IC packages. In this study, data from finite element analysis (FEA) are utilized by machine learning models to predict thermal resistance during package testing. For two package types, namely the Quad Flat No-lead (QFN) and the Thin Fine-pitch Ball Grid Array (TFBGA), data derived from finite element analysis, are employed to predict thermal resistance. The thermal resistance values include θ_JA, θ_JB, θ_JC, Ψ_JT, and Ψ_JB. Five machine learning models, namely the light gradient boosting machine (LGBM), random forest (RF), XGBoost (XGB), support vector regression (SVR), and multilayer perceptron regression (MLP), are applied as forecasting models in this study. Numerical results indicate that the XGBoost model outperforms the other models in terms of forecasting accuracy for almost all cases. Furthermore, the forecasting accuracy achieved by the XGBoost model is highly satisfactory. In conclusion, the XGBoost model shows significant promise as a reliable tool for predicting thermal resistance in packaging design. The application of machine learning techniques for forecasting these parameters could enhance the efficiency and reliability of IC packaging designs. Full article

As semiconductor packaging technologies face limitations, through-silicon via (TSV) technology has emerged as a key solution to extending Moore’s law by achieving high-density, high-performance microelectronics. TSV technology enables enhanced wiring density, signal speed, and power efficiency, and offers significant advantages over traditional wire-bonding techniques. However, achieving fine-pitch and high-density interconnects remains a challenge. Solder flip-chip microbumps have demonstrated their potential to improve interconnect reliability and performance. However, the environmental impact of lead-based solders necessitates a shift to lead-free alternatives. This review highlights the transition from Sn-Pb solders to lead-free options, such as Sn-Ag, Sn-Cu, Sn-Ag-Cu, Sn-Zn, and Bi- or In-based alloys, driven by regulatory and environmental considerations. Although lead-free solders address environmental concerns, their higher melting points pose challenges such as thermal stress and chip warping, which affect device reliability. To overcome these challenges, the development of low-melting-point solder alloys has gained momentum. This study examines advancements in low-temperature solder technologies and evaluates their potential for enhancing device reliability by mitigating thermal stress and ensuring long-term stability. Full article

Electroplating has become a cornerstone technology in semiconductor manufacturing, enabling high-performance interconnects and advanced packaging. Since the introduction of the Damascene Cu process at the 180 nm node, it has evolved to meet the demands for precision, uniformity, and scalability in miniaturized nodes and complex packaging architectures. The shift to horizontal electroplating systems has enhanced uniformity and process stability, particularly for applications such as TSVs, Cu pillars, micro-bumps, and RDLs. Emerging innovations like pulse electroplating, segmented anode control, and AI-driven monitoring are addressing the challenges of fine-pitch interconnects and emerging interconnect materials, such as cobalt. These advancements are critical for high-density interconnects used in AI, HPC, and high-frequency applications. This review explores the advancements in electroplating technologies, focusing on their role in semiconductor manufacturing. It highlights the evolving equipment designs and their implications for achieving precision, scalability, and reliability at advanced nodes. The ongoing development of electroplating equipment and techniques will support the reliability and performance of future semiconductor devices, reinforcing electroplating as a cornerstone technology in advanced packaging and fabrication. Full article

Diacritical Arabic (DA) refers to Arabic text with diacritical marks that guide pronunciation and clarify meanings, making their recognition crucial for accurate linguistic interpretation. These diacritical marks (short vowels) significantly influence meaning and pronunciation, and their accurate recognition is vital for the effectiveness of automatic speech recognition (ASR) systems, particularly in applications requiring high semantic precision, such as voice-enabled translation services. Despite its importance, leveraging advanced machine learning techniques to enhance ASR for diacritical Arabic has remained underexplored. A key challenge in developing DA ASR is the limited availability of training data. This study introduces a transformer-based approach leveraging transfer learning and data augmentation to address these challenges. Using a cross-lingual speech representation (XLSR) model pretrained on 53 languages, we fine-tune it on DA and integrate connectionist temporal classification (CTC) with transformers for improved performance. Data augmentation techniques, including volume adjustment, pitch shift, speed alteration, and hybrid strategies, further mitigate data limitations, significantly reducing word error rates (WER). Our methods achieve a WER of 12.17%, outperforming traditional ASR systems and setting a new benchmark for DA ASR. These findings demonstrate the potential of advanced machine learning to address longstanding challenges in DA ASR and enhance its accuracy. Full article

In this paper, the aim is to optimise the hydrodynamic performance of the novel fin-ring horizontal axis hydrokinetic turbine (HAHK). The original unique fin-ring turbine is an unconventional marine current turbine that comprises seven concentric rings with 88 connecting cambered fins and a solid centre hub. To begin with, the hydrodynamic performance of the benchmark turbine is evaluated using CFD simulations and is validated against sea-test data available in the literature. Subsequently, three of the turbine design parameters, namely, the fins’ pitch angle, the fins’ camber length, and the fins’ aspect ratio, are optimised for maximum power generation. Further test simulations illustrated the existence of a laminar region of flow in the turbine flow field. The K-kL-ω transition-sensitive turbulence model is adopted to capture the influence of transition on the flow field with results compared against those of the fully turbulent K-ε turbulence model. A final fine-tuning in the turbine design is carried out by increasing the number of fins per ring in the outermost rings to further maximise the generated power. The turbine hydrodynamic performance is assessed by comparison against other conventional hydrokinetic turbines available in the literature. Very satisfactory results are obtained with an increase of about 35% in the turbine-generated C_P as compared to that of the benchmark turbine. The turbine performance compares very well with other conventional turbines, especially in terms of higher peak C_P values, wider operating TSR range, and less sensitivity to variations in the inflow current speeds. Full article

With the development of high-density integrated chips, low-k dielectric materials are used in the back end of line (BEOL) to reduce signal delay. However, due to the application of fine-pitch packages with high-hardness copper pillars, BEOL is susceptible to chip package interaction (CPI), which leads to reliability issues such as the delamination of interlayer dielectric (ILD) layers. In order to improve package reliability, the effect of CPI at multi-scale needs to be explored in terms of package integration. In this paper, the stress of BEOL in the flip-chip chip-scale packaging (FCCSP) model during thermal cycling is investigated by using the finite-element-based sub-model approach. A three-dimensional (3D) multi-level finite element model is established based on the FCCSP. The wiring layers were treated by the equivalent homogenization method to ensure high prediction accuracy. The stress distribution of the BEOL around the critical bump was analyzed. The cracking risk of the interface layer of the BEOL was assessed by pre-cracking at a dangerous location. In addition, the effects of the epoxy molding compound (EMC) thickness, polyimide (PI) opening, and coefficient of thermal expansion (CTE) of the underfill on cracking were investigated. The simulation results show that the first principal stress of BEOL is higher at high-temperature moments than at low-temperature moments, and mainly concentrated near the PI opening. Compared with the oxide layer, the low-k layer has a higher risk of cracking. A smaller EMC thickness, lower CTE of the underfill, and larger PI opening help to reduce the risk of cracking in the BEOL. Full article

The mechanical properties of music wire are contingent upon its microstructure, which in turn influences its applications in music. Chinese stringed instruments necessitate exacting standards for comprehensive performance indexes, particularly with regard to the strength, resilience, and rigidity of the musical steel wires, which differ from the Western approach to musical wire. In this study, SWP-B music wire was selected for investigation through metal heat treatment, which was employed to regulate its microstructure characteristics. Furthermore, a spectral analysis was conducted to evaluate the musical expression, encompassing attributes such as pitch and timbre. In conclusion, the governing law of the impact of the microstructure of music wire on its musical expression was established. The results demonstrate that steel wire subjected to a 200 °C annealing treatment for cementite spheroidization can effectively reduce stress concentration, thereby reducing the probability of fracture and consequently improving tonal uniformity and richness while increasing tensile strength from 2578 MPa to 2702 MPa. Conversely, the high-temperature annealing treatment alters the crystalline structure of the material and refines the grain structure, thereby improving the material’s performance and sound quality. The fine microstructure of the music steel wire displays enhanced uniformity. As the annealing temperature increases, the strength of the ferrite phase <110>//ND (<010>//ND, indicating that the <010> direction of the crystal is parallel to the normal direction of the material) and the cementite phase <010>//ND demonstrates a gradual decline. However, this also results in a more pronounced harmonic performance, which, in turn, affects the overall music expression. Full article

Building type information is widely used in various fields, such as disaster management, urbanization studies, and population modelling. Few studies have been conducted on fine-grained building classification in rural areas using China’s Gaofen-7 (GF-7) high-resolution stereo mapping satellite data. In this study, we employed a two-stage method combining supervised classification and unsupervised clustering to classify buildings in the rural area of Pingquan, northern China, based on building footprints, building heights, and multispectral information extracted from GF-7 data. In the supervised classification stage, we compared different classification models, including Extreme Gradient Boosting (XGBoost) and Random Forest classifiers. The best-performing XGBoost model achieved an overall roof type classification accuracy of 88.89%. Additionally, we proposed a template-based building height correction method for pitched roof buildings, which combined geometric features of the building footprint, street view photos, and height information extracted from the GF-7 stereo image. This method reduced the RMSE of the pitched roof building heights from 2.28 m to 1.20 m. In the cluster analysis stage, buildings with different roof types were further classified in the color and shape feature spaces and combined with the building height information to produce fine-grained building type codes. The results of the roof type classification and fine-grained building classification reveal the physical and geometric characteristics of buildings and the spatial distribution of different building types in the study area. The building classification method proposed in this study has broad application prospects for disaster management in rural areas. Full article

Shoulder and elbow injuries are prevalent among baseball players, particularly pitchers, who experience repetitive eccentric loading of the shoulder, leading to muscle damage and increased injury risk. Nearly 40% of shoulder injuries in baseball occur in pitchers, with many facing low rates of return to sport. The rotator cuff (RC) muscles—supraspinatus (SSP), infraspinatus (ISP), subscapularis (SSC), and teres minor (TMin)—are crucial for shoulder stability, movement, and force generation, particularly in overhead sports. Each RC muscle comprises subregions with distinct biomechanical properties, such as strength, moment arm behavior, and activation patterns. These differences allow for a finely tuned balance between joint stability and mobility. For example, the superior subregion of the ISP significantly contributes to external rotation, a function critical in sports like baseball that require precision and power. During pitching, the SSP, ISP, and SSC stabilize the glenohumeral joint through high activation during explosive phases, such as stride, arm cocking, and arm acceleration. Understanding these functional subregional differences is vital for diagnosing and managing shoulder pathologies like RC tears. Despite advancements, clinicians face challenges in predicting re-injury risks and determining return-to-play readiness for athletes with shoulder injuries. Integrating insights into subregional biomechanics with patient care could enhance outcomes. Tailored interventions—whether surgical or rehabilitative—targeting specific subregions could improve recovery times, reduce re-injury risks, and enable more personalized treatment plans. Such approaches are especially beneficial for athletes, older individuals, and those prone to RC injuries, promoting better long-term shoulder health and performance. The present work aims to highlight some of the research on these subregions and their differences, providing insights to enhance treatment approaches for shoulder injuries. Full article