Search Results (46)

To address the need for rapid evaluation of large batches of Mee rough tea during the acceptance stage, this study aims to explore the feasibility of using portable Fourier transform near-infrared (FT-NIR) spectroscopy for preliminary quality screening. The goal is to develop a rapid, non-destructive, and relatively objective assessment method that is applicable to practical acceptance scenarios. This work represents an exploratory proof-of-concept study rather than a finalized industrial grading solution. Spectral data of three reference categories and thirty-six test samples were collected in the wavelength range of 1350–$2500\mathrm{nm}$ using a portable FT-NIR spectrometer. The sample configuration was designed to simulate practical acceptance sampling conditions. The spectra were preprocessed using multiplicative scatter correction, first-order derivative transformation, and mean-centering. Independent principal component analysis (PCA) models were constructed for each reference category to achieve class-wise feature dimensionality reduction, with cumulative explained variance exceeding $95\%$. Distance thresholds were determined using the $3\sigma$ principle based on Euclidean distance and Mahalanobis distance. Classification was performed by distance-based matching between test samples and reference categories. Under optimized matching degree threshold settings of $0.9$ and $0.7$, the two distance models achieved classification accuracies of $86.11\%$ and $83.33\%$, respectively, demonstrating the feasibility of the proposed approach. The main contribution of this study is the application of class-wise PCA combined with distance-based discrimination to the acceptance stage of Mee rough tea. The proposed framework provides a practical exploratory approach for rapid screening and offers a preliminary digital tool to support acceptance decisions. Further validation using larger and more diverse datasets will be necessary prior to large-scale industrial implementation. Full article

After rough planing, defects such as wormholes and small patches of green bark residue and decay are often overlooked and misclassified. Strip-like defects, including splinters and chipped edges, are easily confused with the natural bamboo grain, and a single elongated defect is frequently fragmented into multiple detection boxes. This study proposes a modified TASNet-YOLO model, an improved detector built on YOLO11n. Unlike prior YOLO-based bamboo defect detectors, TASNet-YOLO is a mechanism-guided redesign that jointly targets two persistent failure modes—limited visibility of small, low-contrast defects and fragmentation of elongated defects—while remaining feasible for real-time production settings. In the backbone, a newly designed TriMAD_Conv module is introduced as the core unit, enhancing the detection of wormholes as well as small-area defects such as green bark residue and decay. The additive-gated C3k2_AddCGLU is further integrated at selected C3k2 stages. The combination of additive interaction and CGLU improves channel selection and detail retention, highlighting differences between splinters and chipped edges and bamboo grain strips, thereby reducing false positives and improving precision. In the neck, the neck replaces nearest-neighbor upsampling and CBS with SNI-GSNeck to improve cross-scale alignment and fusion. Under an acceptable real-time budget, predictions for splinters and chipped edges become more contiguous and better aligned to edges, while wormholes predictions are more circular and less noisy. Experiments on our in-house dataset (8445 bamboo-strip defect images) show that, compared with YOLO11n, the proposed model improves detection accuracy by 5.1%, achieves 106.4 FPS, and reduces computational costs by 0.4 GFLOPs per forward pass. These properties meet the throughput demand of 2 m/s conveyor lines, and the compact model size and compute footprint make edge deployment straightforward for fast online screening and preliminary quality grading in industrial production. Full article

Interest in textured surfaces for biomaterials and implants is increasing, with shot peening emerging as a promising method for surface modification. This study investigates the influence of conventional and fine shot peening on the surface morphology, topography, wettability, and antibacterial properties of biomedical-grade Ti6Al4V alloy. Peening was conducted using a custom-built, fully automated system, employing fine (100–200 µm) and coarse (700–1000 µm) shots using well-controlled sets of parameters. Both treatments introduced severe plastic deformation on the surface, resulting in increased roughness. Conventionally shot-peened samples exhibited deeper and wider dimples compared to finely peened ones. Surface wettability shifted from hydrophilic (contact angle: ~4°, untreated) to hydrophobic, reaching contact angles of ~91° and ~100° for fine and conventional shot peening, respectively. Antibacterial assays against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) were evaluated by normalizing colony counts to the untreated Ti6Al4V surface. The inherent antibacterial response of Ti6Al4V against E. coli was preserved after both shot peening treatments, showing no notable increase in bacterial proliferation. In contrast, adhesion of S. aureus increased, more notably on fine shot-peened surfaces, indicating a strain-specific response influenced by surface roughness and wettability. In summary, both fine and conventional shot peening altered the surface morphology, topography, and wettability of Ti6Al4V. At the same time, their antibacterial influence was strain-dependent, underscoring the need for careful parameter selection in biomedical applications. Full article

This study presents a smartphone-based dual-index framework for evaluating bicycle pavement conditions, aimed at supporting sustainable urban mobility and cyclist safety. Conventional assessment methods, such as the International Roughness Index (IRI), often overlook short-range discontinuities and are impractical for micromobility-scale infrastructure monitoring. To address these limitations, two perception-aligned indices were developed: the Bicycle Road Roughness Index (BRI), reflecting sustained surface discomfort, and the Faulting Impact Index (FII), quantifying acute vertical shocks. Both indices were calibrated through structured panel surveys involving 40 experienced cyclists and validated using high-frequency tri-axial acceleration data collected in both experimental and field settings. Regression analysis confirmed strong alignment between sensor signals and user perception (R² = 0.74 for BRI; R² = 0.76 for FII). A five-grade classification system was proposed, with critical FII thresholds at 87.3 m/s² for “risky” and 119.4 m/s² for “not rideable” conditions. Field validation across four diverse sites revealed over 380 hazard segments requiring attention, demonstrating the framework’s ability to identify localized risks that may be masked by traditional metrics. By leveraging off-the-shelf smartphones and open-source sensing tools, the proposed approach enables scalable, low-cost, and cyclist-centered diagnostics. The dual-index system not only enhances rideability evaluation but also supports targeted maintenance planning, real-time hazard detection, and broader efforts toward data-driven, sustainable micromobility management. Full article

Objective: to evaluate the advantages and disadvantages of injection laryngoplasty with hyaluronic acid in patients older than 65 years with presbyphonia. Study Design: a retrospective observational study. Setting: an academic secondary medical center. Methods: This study was performed using a group of patients diagnosed with presbyphonia who were treated using injection laryngoplasty with hyaluronic acid and underwent a minimum follow-up of 12 months. Subjective parameters such as the Voice Handicap Index–10 (VHI-10) and the GRBAS scale (grade, roughness, breathiness, asthenia, strain) were measured, as well as objective parameters such as the closure defect area. The medical records of patients undergoing this procedure during the 2020–2023 period were reviewed. An analysis of the demographic and clinical variables of the group was performed, as well as the values of the VHI-10, GRBAS, difference, and improvement of the area of closure defect before and after the procedure, along with the treatment duration and sensation of improvement. Results: The mean pre- and postoperative VHI-10 decreased from 26.8 to 19.6, showing significant differences (p = 0.007). The postoperative GRBAS mean score was 5.6 and normality can be assumed when it is below 9. Out of the 16 patients, 11 of them reported subjective improvement in their symptoms. More than half of them showed an improvement in the closure defect greater than 80%, with a significant reduction in the area (p < 0.001). Conclusions: hyaluronic acid injection in patients with presbyphonia produced a clear subjective improvement in voice quality and a decrease in the closure defect area. Full article

The Münchberg Gneiss Complex (Central European Variscides, Germany) is separated by a deep-seated lineamentary fault zone, the Franconian Lineamentary Fault Zone, from its Mesozoic foreland. The study area offers insight into a great variety of landforms created by fluvial and mass wasting processes together with their bedrocks, covering the full range from unmetamorphosed sediments to high-grade regionally metamorphic rocks. It renders the region an ideal place to conduct a study of compositional and numerical geomorphology and their landscape-forming indices and parameters. The landforms under consideration are sculpted out of the bedrocks (erosional landforms) and overlain by depositional landforms which are discussed by means of numerical landform indices (LFIs), all of which are coined for the first time in the current paper. They are designed to be suitable for applied geosciences such as extractive/economic geology as well as environmental geology. The erosional landform series are subdivided into three categories: (1) The landscape roughness indices, e.g., VeSi_val (vertical sinuosity—valley of landform series) and the VaSlAn_alti (variation in slope angle altitude), which are used for a first order classification of landscapes into relief generations. The second order classification LFIs are devoted to the material properties of the landforms’ bedrocks, such as the rock strength (VeSi_lith) and the bedrock anisotropy (VaSlAn_norm). The third order scheme describes the hydrography as to its vertical changes by the inclination of the talweg and the different types of knickpoints (IncTal_lith/grad) and horizontal sinuosity (HoSi_lith/grad). The study area is subjected to a tripartite zonation into the headwater zone, synonymous with the paleoplain which undergoes some dissection at its edge, the step-fault plain representative of the track zone which undergoes widespread fluvial piracy, and the foreland plains which act as an intermediate sedimentary trap named the deposition zone. The area can be described in space and time with these landform indices reflecting fluvial and mass wasting processes operative in four different stages (around 17 Ma, 6 to 4 Ma, <1.7 Ma, and <0.4 Ma). The various groups of LFIs are a function of landscape maturity (pre-mature, mature, and super-mature). The depositional landforms are numerically defined in the same way and only differ from each other by their subscripts. Their set of LFIs is a mirror image of the composition of depositional landforms in relation to their grain size. The leading part of the acronym, such as QuantSan_heav and QuantGrav_lith, refers to the process of quantification, the second part to the grain size, such as sand and gravel, and the subscript to the material, such as heavy minerals or lithological fragments. The three numerical indices applicable to depositional landforms are a direct measurement of the hydrodynamic and gravity-driven conditions of the fluvial and mass wasting processes using granulometry, grain morphology, and situmetry (clast orientation). Together with the previous compositional indices, the latter directly translate into the provenance analysis which can be used for environmental analyses and as a tool for mineral exploration. It creates a network between numerical geomorphology, geomorphometry, and the E&E issue disciplines (economic/extractive geology vs. environmental geology). The linguistics of the LFIs adopted in this publication are designed so as to be open for individual amendments by the reader. An easy adaptation to different landform suites worldwide, irrespective of their climatic conditions, geodynamic setting, and age of formation, is feasible due to the use of a software and a database available on a global basis. Full article

As an effective method for uncertain knowledge discovery and decision-making, the three-way decisions model has attracted extensive attention from scholars. However, in practice, the existing sequential three-way decision model often faces challenges due to factors such as missing data and unbalanced attribute granularity. To address these issues, we propose an intuitionistic fuzzy sequential three-way decision (IFSTWD) model, which introduces several significant contributions: (1) New intuitionistic fuzzy similarity relations. By integrating possibility theory, our model defines similarity and dissimilarity in incomplete information systems, establishing new intuitionistic fuzzy similarity relations and their cut relations. (2) Granulation method innovation. We propose a density neighborhood-based granulation method to partition decision attributes and introduce a novel criterion for evaluating attribute importance. (3) Enhanced decision process. By incorporating sequential three-way decision theory and developing a multi-level granularity structure, our model replaces the traditional equivalent relation in the decision-theoretic rough sets model, thus advancing the model’s applicability and effectiveness. The practical utility of our model is demonstrated through an example analysis of “Chinese + vocational skills” talent competency and validated through simulation experiments on the UCI dataset, showing superior performance compared to existing methods. Full article

The evaluation of the shrinkage–swelling characteristic of expansive clay is of great significance, but it is a complex problem since the evaluation process involves numerous uncertain factors, such as randomness, non-subordination, and hesitation uncertainties. Here, an intuitionistic connection cloud model has been proposed to address this issue. First, an evaluation index system is established. According to the reliability of interval-valued evaluation indexes, the corresponding cloud numerical characteristic parameters are specified based on the membership interval generated by the intuitionistic fuzzy principle. Moreover, the improved conditional information entropy based on rough set theory is utilized to assign the index weight. Subsequently, combined with the weight, the intuitionistic connection degree of the sample to the classification standard is determined to identify the shrinkage–swelling grade. Finally, a case study on the shrinkage–swelling grade of untreated and lime-treated expansive clays in Hefei Xinqiao International Airport was performed to illustrate the validity and reliability of the model. The results show that the proposed model is reasonable and feasible for the evaluation of the shrinkage–swelling grade of untreated and lime-treated expansive clays. Full article

Additive manufacturing (AM) technologies have advanced from rapid prototyping to becoming viable manufacturing solutions, offering users both design flexibility and mechanical properties that meet ISO/ASTM standards. Powder bed fusion using a laser beam (PBF-LB), a popular additive manufacturing process (aka 3D printing), is used for the cost-effective production of high-quality products for the medical, aviation, and automotive industries. Despite the growing variety of metallic powder materials available for the PBF-LB process, there is still a need for new materials and procedures to optimize the processing parameters before implementing them into the production stage. In this study, we explored the use of a checkerboard scanning strategy to create samples of various sizes (ranging from 130 mm³ to 8000 mm³ using parameters developed for a small 125 mm³ piece). During the PBF-LB process, all samples were fabricated using Ti grade 2 and were in situ alloyed with a precisely controlled amount of oxygen (0.1–0.4% vol.) to enhance their mechanical properties using a solid solution strengthening mechanism. The samples were fabricated in three sets: I. Different sizes and orientations, II. Different scanning strategies, and III. Rods for high-cycle fatigue (HCF). For the tensile tests, micro samples were cut using WEDM, while for the HCF tests, samples were machined to eliminate the influence of surface roughness on their mechanical performance. The amount of oxygen in the fabricated samples was at least 50% higher than in raw Ti grade 2 powder. The O₂-enriched Ti produced in the PBF-LB process exhibited a tensile strength ranging from 399 ± 25 MPa to 752 ± 14 MPa, with outcomes varying based on the size of the object and the laser scanning strategy employed. The fatigue strength of PBF-LB fabricated Ti was 386 MPa, whereas the reference Ti grade 2 rod samples exhibited a fatigue strength of 312 MPa. Our study revealed that PBF-LB parameters optimized for small samples could be adapted to fabricate larger samples using checkerboard (“island”) scanning strategies. However, some additional process parameter changes are needed to reduce porosity. Full article

Efficiently managing multiple process parameters is critical for achieving optimal performance in additive manufacturing. This study investigates the relationship between eight key parameters in fused deposition modeling (FDM) and their impact on responses like average surface roughness (Ra), tensile strength (TS), and flexural strength (FS) of carbon fiber-reinforced polyamide 12 (PA 12-CF) material. The study integrates response surface methodology (RSM), grey relational analysis (GRA), and grey wolf optimization (GWO) to achieve this goal. A total of 51 experiments were planned using a definitive screening design (DSD) based on response RSM. The printing process parameters, including layer thickness, infill density, and build orientation, significantly affect Ra, TS, and FS. GRA combines responses into a single measure, grey relational grade (GRG), and a regression model is developed. GWO is then employed to optimize GRG across parameters. Comparison with GRA-optimized parameters demonstrates GWO’s ability to discover refined solutions, reducing average surface roughness to 4.63 μm and increasing tensile strength and flexural strength to 88.5 MPa and 103.12 MPa, respectively. Practical implications highlight the significance of GWO in industrial settings, where optimized parameters lead to reduced costs and improved product quality. This integrated approach offers a systematic methodology for optimizing FDM processes, ensuring robustness and efficiency in additive manufacturing applications. Full article

The current standard for evaluating road conditions worldwide relies primarily on the Pavement Condition Index (PCI) and the International Roughness Index (IRI). The IRI can be further calculated to obtain the Riding Quality Index (RQI). To assess pavement damage, various imaging equipment is commonly utilized, providing consistent results that align with actual road conditions. For roughness detection, the Laser Profilometer offers excellent results but may not be suitable for rural roads with poor conditions due to its high inspection cost and the need for a stable environmental setting. Therefore, there is a pressing need to develop cost-effective, rapid, and accurate roughness inspection methods for these roads, which constitute a significant portion of the road network. This study examined the relationship between PCI and RQI using nonlinear regression on 30,088 valid pavement inspection records from various regions in China (totaling 24,624.222 km). Our objective was to estimate RQI solely from PCI data, capitalizing on its broad coverage and superior accuracy. Additionally, we explored how PCI levels impact RQI decay rates. The models in this study were compared to several models published in previous studies at last. Our findings indicate that the model performs best for low-grade roads with low PCI scores, achieving over 90% accuracy for both cement concrete and asphalt concrete pavements. Furthermore, different levels of pavement damage have distinct effects on RQI decay rates, with the most significant impact observed when the pavement is severely damaged. The models in this study outperformed all the other available models in the literature. Consequently, under limited inspection conditions in rural areas, pavement damage inspection results can effectively predict riding quality or roughness, thereby reducing inspection costs. Overall, this study offers valuable insights but has limitations, including limited global generalizability and the model’s applicability to high-grade roads. Future research is needed to address these issues and enhance practical applications. Full article

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO₂/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO₂/Gr composites were made from stir casting with 6-weight percent ZrO₂ as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L₂₇ OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (K_w) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO₂ with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (T_off) of 40 µs, a pulse on time (T_on) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response. Full article

The Decision-Theoretic Rough Set model stands as a compelling advancement in the realm of rough sets, offering a broader scope of applicability. This approach, deeply rooted in Bayesian theory, contributes significantly to delineating regions of minimal risk. Within the Decision-Theoretic Rough Set paradigm, the universal set undergoes a tripartite division, where distinct regions emerge and losses are intelligently distributed through the utilization of membership functions. This research endeavors to present an enhanced and more encompassing iteration of the Decision-Theoretic Rough Set framework. Our work culminates in the creation of the Generalized Intuitionistic Decision-Theoretic Rough Set (GI-DTRS), a fusion that melds the principles of Decision-Theoretic Rough Sets and intuitionistic fuzzy sets. Notably, this synthesis bridges the gaps that exist within the conventional approach. The innovation lies in the incorporation of an error function tailored to the hesitancy grade inherent in intuitionistic fuzzy sets. This integration harmonizes seamlessly with the contours of the membership function. Furthermore, our methodology deviates from established norms by constructing similarity classes based on similarity measures, as opposed to relying on equivalence classes. This shift holds particular relevance in the context of aggregating information systems, effectively circumventing the challenges associated with the process. To demonstrate the practical efficacy of our proposed approach, we delve into a concrete experiment within the information technology domain. Through this empirical exploration, the real-world utility of our approach becomes vividly apparent. Additionally, a comprehensive comparative analysis is undertaken, juxtaposing our approach against existing techniques for aggregation and decision modeling. The culmination of our efforts is a well-rounded article, punctuated by the insights, recommendations, and future directions delineated by the authors. Full article

Mineral resource-based cities have formed a large number of goafs due to the long-term mining of coal. It is of great significance to make full use of the abandoned land resources above the goaf to promote the transformation and development of resource-based cities. In order to avoid the threat of surface residual deformation to the proposed construction project, it is an urgent problem to obtain the stability results of the construction site accurately. First of all, based on the principles of relevance, hierarchy, representativeness and feasibility of index selection, 10 indexes are selected to construct the stability evaluation index system. Then the subjective weight and objective weight of evaluation indexes are determined based on improved AHP, rough set and CRITIC methods, which improves the accuracy of the determination of the index weights. In addition, the membership degree of each index is determined using the cloud model. Finally, the stability grade can be obtained according to the maximum membership degree theory. The above researches are applied to evaluate the stability of the Mianluan expressway construction site, and the results show that the stability level of the study area is not uniform and that there are two states: stable and basically stable. Finally, a sensitivity analysis of the subjective weight of each index is carried out, the index stopping time has the highest sensitivity to weight (12.44%), which is far lower than the corresponding weight change rate of 100%, indicating that the determination of weight is scientific and reasonable. These things considered, the reliability of the evaluation result is indirectly verified according to the field leveling. This research can provide a reference for the effective utilization of land resources above an old goaf. Full article

The surface characteristics and friction behaviour of titanium Grade 2 with modified nitride (TiN, Ti₂N) and boride (TiB) compound layers were investigated. It was shown that during non-contact boriding in oxygen-containing medium of titanium, the diffusion processes take place mainly by the interscale mechanism; however, during nitriding, besides the traditional interscale diffusion mechanism, the grain boundary mechanism of diffusion of nitrogen atoms is also realized. The optimal set of surface roughness parameters (height and step parameters, a combination of kurtosis and asymmetry, and profile reference curve parameters) was obtained after boriding. It was determined that the intensity of the adhesive wear of the tribo-pairs with stainless steel and ultrahigh molecular weight polyethylene under dry sliding conditions was influenced not only by the hardness but also roughness of the modified surface layer. The lowest friction coefficient was fixed for the TiB compound layer in both tribo-pairs. Full article