Appl. Sci., Volume 13, Issue 17 (September-1 2023) – 509 articles

Base45 encodes pairs of octets using 3 characters from an alphabet of 45 printable symbols. Previous works showed the ability to hide payload data into encoded strings by exploiting the unused configurations of the Base45 encoding. In this paper, we present Hide45, an algorithm for hiding data into Base45 encoded strings that optimizes the embedding capacity, according to the frequency distribution of the input data. Experimental tests show that an optimal assignment of bit configurations to the most frequent pairs of octets allows to reach a payload capacity very close to the theoretical capacity of the method, improving over a baseline assignment by up to 53%. Full article

X-ray diffraction (XRD) is a proven, powerful technique for determining the phase composition, structure, and microstructural features of crystalline materials. The use of machine learning (ML) techniques applied to crystalline materials research has increased significantly over the last decade. This review presents a survey of the scientific literature on applications of ML to XRD data analysis. Publications suitable for inclusion in this review were identified using the “machine learning X-ray diffraction” search term, keeping only English-language publications in which ML was employed to analyze XRD data specifically. The selected publications covered a wide range of applications, including XRD classification and phase identification, lattice and quantitative phase analyses, and detection of defects and substituents, as well as microstructural material characterization. Current trends in the field suggest that future efforts pertaining to the application of ML techniques to XRD data analysis will address shortcomings of ML approaches related to data quality and availability, interpretability of the results and model generalizability and robustness. Additionally, future research will likely incorporate more domain knowledge and physical constraints, integrate with quantum physical methods, and apply techniques like real-time data analysis and high-throughput screening to accelerate the discovery of tailored novel materials. Full article

Significant thermochemical nonequilibrium effects always exist in the flow field around hypersonic vehicle at extreme flight condition. Previous studies have proposed various thermodynamic and chemical kinetic models to describe the thermochemical nonequilibrium processes in hypersonic and high-temperature flow. However, different selections from such models might lead to remarkable variations in computational burden and prediction accuracy, which is still a matter of being unclear. In the present study, different commonly studied models for calculating the thermochemical nonequilibrium are systematically evaluated. The 5-, 7- and 11-species chemical kinetic models of Dunn-Kang, Gupta and Park together with the one- and two-temperature models are employed respectively to simulate the hypersonic flows over a standard cylinder with the radius of 1 m by HyFLOW, which is a commercial software based on the numerical solution of Navier-Stokes equations. Three flight conditions of FIRE Ⅱ classical flight trajectory are employed in the study. It shows that the differences between the results of the Dunn-Kang, Gupta and Park chemical kinetic models with the same number of species are small, but the Gupta model predicts the most conservative values of the wall heat flux. When only the order of magnitude and distribution trends of the pressure and wall heat flux are concerned, the one-temperature model combined with 5-species chemical reaction model can be used for a rapid prediction. While the accurate flow solution is required, the two-temperature model conjugated with Gupta 11-species model is recommended, especially at the conditions of extremely high altitude and Mach number. Full article

The fatigue safety of cable-girder anchorage structures in cable-stayed bridges under long-term service has attracted much attention. For bridges located in seasonally cold regions, the effect of low-temperature environments should be considered when evaluating fatigue performance. Using the Heilongjiang Bridge in China as a case study, a room-temperature fatigue test with a numerical simulation that considers the low-temperature effect on both load effect and fatigue resistance was proposed. A fatigue test with increased testing load amplitude was performed on a 1:3.75 ratio specimen. After 3.2 million loading cycles and using an acoustic emission technique, no fatigue crack was observed in the anchorage structure. The extended finite element method was then adopted to analyze the anchorage zone’s fatigue crack initiation position and propagation path. Finally, based on the fatigue characteristics of bridge steel, the fatigue resistance to the crack propagation of the vulnerable area was evaluated under three different service conditions. The results show that the fatigue performance of the anchorage zone at low temperatures is sufficient. Moreover, this paper provides a more widely applicable and cost-effective approach for the fatigue evaluation of steel bridges. Full article

Alternative methods of presenting the information contained in mathematical images, which are adapted to the needs of blind people, are significant challenges in modern education. This article presents an alternative multimodal method that substitutes the sense of sight with the sense of touch and hearing to convey graphical information. The developed method was evaluated at a center specializing in the education of the blind in Poland, on a group of 46 students aged 15–19. They solved a set of 60 high school-level problems on geometry, mathematical analysis, and various types of graphs. We assessed the mechanisms introduced for the sense of touch and hearing, as well as the overall impression of the users. The system usability scale and the NASA task load index tests were used in the evaluation. The results obtained indicate an overall increase in user satisfaction and usefulness of the proposed approach and a reduction in the workload during exercise solving. The results also show a significant impact of the proposed navigation modes on the average time to reach objects in the drawing. Therefore, the presented method could significantly contribute to the development of systems supporting multimodal education for people with blindness. Full article

Due to the high cost and the predicted shortage of rare earth elements in the near future, the task of developing energy-efficient electric machines without rare earth magnets is of great importance. This article presents a comparative analysis of optimized designs of a ferrite-assisted synchronous reluctance machine (FaSynRM) and a ferrite-assisted synchronous homopolar machine (FaSHM) in a 370-kW subway train drive. The objectives of optimizing these traction machines are to reduce their losses, maximum armature current, and torque ripple. The optimization considers the characteristics of the machines in the subway train moving cycle. The problem of the risk of irreversible demagnetization of ferrites in the FaSynRM and FaSHM is also considered. To reduce the computational burden, the Nelder-Mead method is used for the optimization. It is shown that the FaSHM demonstrates better field weakening capability, which can reduce the maximum current, power, and cost of the inverter power modules. At the same time, the FaSynRM requires less permanent magnet mass for the same torque density and is more resistant to irreversible demagnetization, which can reduce costs and improve the reliability of the electric machine. Full article

Wheat production safety is facing serious challenges because wheat yellow rust is a worldwide disease. Wheat yellow rust may have no obvious external manifestations in the early stage, and it is difficult to detect whether it is infected, but in the middle and late stages of onset, the symptoms of the disease are obvious, though the severity is difficult to distinguish. A traditional deep learning network model has a large number of parameters, a large amount of calculation, a long time for model training, and high resource consumption, making it difficult to transplant to mobile and edge terminals. To address the above issues, this study proposes an optimized GhostNetV2 approach. First, to increase communication between groups, a channel rearrangement operation is performed on the output of the Ghost module. Then, the first five G-bneck layers of the source model GhostNetV2 are replaced with Fused-MBConv to accelerate model training. Finally, to further improve the model’s identification of diseases, the source attention mechanism SE is replaced by ECA. After experimental comparison, the improved algorithm shortens the training time by 37.49%, and the accuracy rate reaches 95.44%, which is 2.24% higher than the GhostNetV2 algorithm. The detection accuracy and speed have major improvements compared with other lightweight model algorithms. Full article

This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud Data (PCD) of Airborne Laser Scanning (ALS). Advanced scanning techniques capture detailed geometry from the physical site and generate high-resolution point clouds, which are processed to create 3D models for GIS integration. The critical contribution of this research lies in a scalable Scan to BIM mapping process, which can be used for generating building footprints and masses, including attributes, on 3D GIS. The resulting integrated BIM–GIS dataset provides an accurate building mass, facade information, facility asset management, and architectural design and facilitates improved decision-making in urban planning based on enhanced visualization, analysis, and simulation. This study suggests a flexible Scan to BIM mapping process description based on use cases, including algorisms. Through prototype development, a case study demonstrates the effectiveness of the process approach, the automatic generation of BIM on a 3D GIS platform, and reducing the manual efforts. The proposed method automatically creates DEM, SHP, GeoJSON, IFC, and coordinate system information from scan data and can effectively map building objects in 3D GIS. Full article

Overhead hoist transportation systems (OHTS) have been the subject of worldwide research and development in recent years. The majority of these systems are utilized in semi-automated or fully automated factories. This article proposes a new solution for OTHS based on the concept of the modulation of mobile units that can move on a railway structure from one point to another. The OHTS mentioned in this article is a group of shuttles that can operate independently but which also have the ability to cooperate together to complete the desired tasks. By using the space below the ceiling, this system can operate without affecting the original design of the factories. There are many potential fields of application for picking-up and delivering, such as the medical field, the food and beverage fields, automotive and electrical appliances, etc. Moreover, by applying Dijkstra’s algorithm in the controller design, the transportation speed among the stations in the whole system can be improved. The real prototype of the whole system, including three shuttles, is also manufactured to explore and assess the design and operation of the proposed system and its controller. Full article

Eucalyptus globulus leaves contain various types of phenolic metabolites related to their antioxidant effects such as acids, catechin, flavonoids, and others. To optimize its antioxidative phenolic contents, E. globulus was extracted under various solvent conditions using 0, 10, 30, 50, 70, 90, and 100% ethanol. The 50% ethanol extract possessed the highest content of total phenolics with 497.7 mg GAE (gallic acid equivalent)/g extract. In contrast, the highest content of total flavonoids was evaluated in the 100% ethanol extract, having 169.3 mg QE (quercetin equivalent)/g extract. The antioxidant activity of various extraction conditions was assessed against the radical scavenging effect of DPPH (SC₅₀ = 188.2~5841.7 μg/mL) and ABTS (SC₅₀ = 14.2~171.3 μg/mL). The major chemical composition of E. globulus leaves was identified as including salicylic acid β-D-glucuronide (1), chlorogenic acid (2), epicatechin (3), 2″-O-galloylhyperin (4), isoquercitrin (5), isorhapontin (6), quercitrin (7), and quercetin-3-O-glucuronide (8) using LC-Q-TOF/MS analysis. Among them, the identified metabolites were clarified and their contents in the extracts were calculated via quantitative analysis using HPLC at 254 nm. The flavonoids (4, 5, 7, and 8) were determined to have an influence on the TPC, TFC, and antioxidant activity of E. globulus leaves. The results suggested that optimizing the extraction conditions can result in appropriate chemical composition and antioxidant activity. Full article

Deep learning has experienced an increased demand for its capabilities to categorize and optimize operations and provide higher-accuracy information. For this purpose, the implication of deep learning procedures has been described as a vital tool for the optimization of supply chain firms’ transportation operations, among others. Concerning the indexes of transportation operations of supply chain firms, it has been found that the contribution of big data analytics could be crucial to their optimization. Due to big data analytics’ variety and availability, supply chain firms should investigate their impact on their key transportation indexes in their effort to comprehend the variation of the referred indexes. The authors proceeded with the gathering of the required big data analytics from the most established supply chain firms’ websites, based on their (ROPA), revenue growth, and inventory turn values, and performed correlation and linear regression analyses to extract valuable insights for the next stages of the research. Then, these insights, in the form of statistical coefficients, were inserted into the development of a Hybrid Model (Agent-Based and System Dynamics modeling), with the application of the feedforward neural network (FNN) method for the estimation of specific agents’ behavioral analytical metrics, to produce accurate simulations of the selected key performance transportation indexes of supply chain firms. An increase in the number of website visitors to supply chain firms leads to a 60% enhancement of their key transportation performance indexes, mostly related to transportation expenditure. Moreover, it has been found that increased supply chain firms’ website visibility tends to decrease all of the selected transportation performance indexes (TPIs) by an average amount of 87.7%. The implications of the research outcomes highlight the role of increased website visibility and search engine ranking as a cost-efficient means for reducing specific transportation costs (Freight Expenditure, Inferred Rates, and Truckload Line Haul), thus achieving enhanced operational efficiency and transportation capacity. Full article

Breast cancer is a generalized global problem. Biomarkers are the active substances that have been considered as the signature of the existence and evolution of cancer. Early screening of different biomarkers associated with breast cancer can help doctors to design a treatment plan. However, each screening technique for breast cancer has some limitations. In most cases, a single technique can detect a single biomarker at a specific time. In this study, we address different types of biomarkers associated with breast cancer. This review article presents a detailed picture of different techniques and each technique’s associated mechanism, sensitivity, limit of detection, and linear range for breast cancer detection at early stages. The limitations of existing approaches require researchers to modify and develop new methods to identify cancer biomarkers at early stages. Full article

Xiong’an New Area is a national event and a project planned for a millennium of China. Its high-quality construction is of great significance to easing the noncapital functions of Beijing and the coordinated development of the Beijing-Tianjin-Hebei region. As an emerging city, the development and construction of Xiong’an New Area is bound to be restricted by geological and resource conditions. Therefore, geo-environment suitability analysis is the necessary basis of urban development and construction. Geo-environment suitability analysis of urban construction is a complex process that requires various geological indicator information, and relevant expertise to analyze their relevance. This paper focuses on the analytic hierarchy process (AHP) for the assessment of geo-environment suitability for urban construction in Rongcheng district, which is a Start Construction Region in Xiong’an New Area. Multiple factors, including the characteristic value of bearing capacity of foundation soil, land subsidence rate, geological faults, ground fissures, potential liquefied sands, quality of groundwater chemistry, quality of soil chemistry, chemical corrosion of concrete by groundwater, chemical corrosion of steel by groundwater, and enrichment of deep groundwater and geothermal resource, were used for the suitability assessments. From the evaluation achievements, the high and very high suitable lands for urban construction, with an acreage percentage of 89.2%, were located in most parts of the study area. Meanwhile, for another 9.1% of the land, the impacts of geological faults, land subsidence, and potential liquefied sands needed to be noted preferentially for urban construction. Full article

This study summarizes the engineering design and calculation methods of micropiles and proposes a pile length optimization model based on numerical simulation software. Based on the proposed micropile calculation method and optimization method, a specific analysis of a project example was carried out, and a series of calculations, such as micropile design calculation and pile length optimization for the project, was completed. The results show that the miniature pile length optimization model based on numerical simulation finite difference method improves the previous method by automating the optimization process through fast modeling, automatic creation of optimization commands, and output and analysis of optimization results, and realizes the optimization of pile length using numerical simulation, which improves the efficiency of the optimization of the pile length under the premise of guaranteeing accuracy, and achieves the unity of both efficiency and accuracy. The feasibility of this optimization process is proved by engineering examples. The engineering practicability of the micropile design calculation method and optimization method proposed in this study is proved through practice. It provides a reference value for the initial fast and flexible management of small landslides. Full article

In this study, we aimed to evaluate the effectiveness of a brain robot in rehabilitation that combines motor imagery (MI), robotic motor assistance, and electrical stimulation. Thirteen in-patients with severe post-stroke hemiplegia underwent electroencephalography (EEG), measured according to the international 10–20 method, during MI. The dicephalus robotic system (DiC) was activated by detecting event-related desynchronization (ERD) using the Markov switching model (MSM) and relative power (RP) from the EEG of the motor cortex (C3 and C4). The reaction times (the time between ERD detection and DiC activation) of the MSM and RP were compared using Wilcoxon’s signed rank sum test. ERD was detected in all 13 and 12 patients with the MSM and RP, respectively. The DiC reaction time for the ERD detection process was significantly shorter for the MSM (13.02 ± 0.16 s) than for the RP (19.95 ± 7.45 s) (W = 9, p = 0.0037). The results of this study suggest that ERD responses can be detected in the motor cortex during MI in patients with severe upper-extremity paralysis; the MSM is more effective than the RP in detecting ERD when the EEG signal is used as a switch to activate the robot, and the reaction time to detect the signal is shorter. Full article

In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused prediction model-based deep learning with a detection model-based Internet of Things. This study utilized parameters, namely, overall prediction performance measures based on a confusion matrix, to assess the performance of the framework in addition to its ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, the framework reduced the risk probability from 1.51 × 10⁻³ to 8.57 × 10⁻⁹. Our findings demonstrate the high prediction accuracy of the framework, which also offers a reliable decision-making mechanism for providing early warning and reducing the potential hazards of rock falls. Full article

Radiation therapy for treating shallow tumors is challenging, necessitating the use of boluses. This study introduces the first application of the life-casting method to fabricate patient-specific bolus molds from gypsum sheets, comparing them with commercial boluses. Our developed boluses reduced the air gap between the skin and bolus by 77.62% compared to that of commercial boluses. In vivo dosimetry using the patient-specific bolus demonstrated better results compared to using a commercial bolus. When using the commercial bolus, the mean %Diff and max %Diff were 1.10 ± 0.61%, respectively, and 2.00% for three-dimensional conformal radiation therapy (3D-CRT) and 7.19 ± 1.90% and 10.14% for volumetric modulated arc therapy (VMAT), respectively. Contrastingly, our developed bolus demonstrated more accurate dose delivery with a mean %Diff and max %Diff of 0.82 ± 0.61% and 1.69% for 3D-CRT and 3.42 ± 1.01% and 5.03% for VMAT, respectively. Furthermore, the standard deviation between the measurements was more than 50% lower when using a patient-specific bolus than when using a commercial bolus. These results show that our bolus reduces air gaps, improves the accuracy of bolus positioning, and enhances the precision of dose delivery compared with the performance of commercial boluses. Therefore, the developed bolus is expected to be valuable in clinical applications. Full article

The effectiveness of a cruise ship’s emergency evacuation is greatly influenced by the way people interact; this paper uses the social force model to simulate two different evacuation scenarios considering the impact of small groups. It uses an agent to simulate the behavior of a single occupant, and leverages the social force model to quantify the effect of group behavior on the group members. According to the influence of the group on the members, this paper corrects the expected speed of the members to determine the speed of crowd evacuation. It uses the SAFEGUARD cruise ship as the evacuation platform to simulate the process of evacuating the passengers to the boarding station and assembly station, respectively, and calculates the evacuation time, congestion area, and congestion duration of passengers under the action of groups. The simulation results of the two scenarios show that the group effect increases the average evacuation time by 15.29% and 21.79%, and increases the average detour distance by 24.54% and 17.89%, respectively. Full article

Static guided surgery for dental implant insertion is a well-documented procedure requiring the manufacturing of a custom-made surgical guide, either teeth-supported, mucosal-supported, bone-supported, or mixed (teeth-mucosal-supported), depending on the clinical situation. The guidance of the surgical drills during implant bed preparation could be undertaken using a sequence of different diameters of metal drill sleeves or, with the sleeves incorporated in the surgical guide, shank-modified drills, both clinically accepted and used with good results. Despite the great number of advantages associated with the use of guided surgery, one of the major risks is guide fracture during drilling for implant bed preparation. Therefore, the aim of the present study was to evaluate the surgical guides without metal sleeves and to simulate, with the aid of Finite Element Analysis (FEA), the use of such dentally supported guides for implant insertion. The FEA is performed in CATIA v5 software after defining the surgical guide mesh material and bone properties. A maximum stress of 6.92 MPa appeared on the guide at the special built-in window meant to allow cooling during drilling, and the maximum value of the guide displacement during drilling simulation was 0.002 mm. Taking into consideration the limits of the current research, the designed tooth-supported surgical guide can withstand the forces occurring during the surgery, even in denser bone, without the risk of fracture. Full article

This study aims to address the challenge of implementing Lean philosophy in Small and Medium Enterprises (SMEs) and fill the research gap regarding Lean application in vehicle seat upholstery maintenance/repairing processes. The Lean tools applied in a case study of an upholstery industry of vehicle seats were as follows: Value Stream Mapping, Spaghetti Diagram, Gemba, 5S, Standardized Work, Kaizen, Kanban, and Poka-Yoke tools. A Decision Support Method using Excel Microsoft 365 was developed for improved stock control. A GUT Matrix was formulated to prioritize improvement opportunities, aiding prompt decision-making. This systematic approach enabled the company to address critical areas requiring swift attention. The results of Lean tools implementation led to a process waste minimization around 47%, and the process Lead Time decreased by approximately 26%, resulting in a 33% production increase. Thus, the Lean tools integration leads to substantial waste reduction, shorter process time, and increased production. The Decision Support Method enabled the company to efficiently monitor and manage its stock levels, thereby enhancing inventory management practices. This case study outlines the successful optimization of an upholstery production process in an SME by effectively applying Lean tools, highlighting its feasibility and benefits. Full article

Current construction codes require detailed analyses for structural retrofitting, which must consider performance during seismic events. Therefore, the computational models used to evaluate existing infrastructure require nonlinear structural analysis and damage estimates. For structural retrofitting, nonlinear computational modeling must represent the connectivity between existing and new elements. This study proposes recommendations on structural modeling based on fiber elements to represent reinforced concrete (RC) moment frames retrofitted with mortar walls reinforced with steel wire mesh. For this purpose, capacity curves of moment frames retrofitted with mortar walls were calculated by hand with the Bernoulli–Euler beam theory, moment–curvature analyses, and a plastic hinge model. Then, these capacity curves were used to calibrate the connectivity and constraint conditions in fiber models between the existing frame and the new wall required to capture the performance of the retrofitted structure. The study found that, for a single wall connected with top and bottom frame border elements, the capacity curves from fiber models underestimate stiffness, maximum strength, and residual strength. These estimation issues are reduced by including intermediate connectivity nodes between the top and bottom frame where rigid link constraints connect the existing frame with the new wall. Full article

Additive manufacturing (AM) or additive layer manufacturing (ALM), defined by the International Organization for Standardization and American Society of Testing and Materials (ISO/ASTM 52900) as the “process of joining materials to make parts from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing and formative manufacturing methodologies” [...] Full article

The paper presents the problem of generation and validation of Velocity Interval Depth (VID) models with the application of non-seismic geophysical and geological data. The study area is a part of the Carpathian Foredeep located close to its contact with the Carpathian Overthrust. In this area of complicated geological structure, hydrocarbon deposits have been successfully explored for decades with seismic methods and drilling. The research applied the Simultaneous Joint Inversion (SJI) of independent geophysical data, which is a modern methodology of geophysical data processing, that is still under development. Such an attempt was necessary due to the lack of a sufficiently dense grid of wells in the study area, in which seismic velocities would be correctly recorded. Such data would be then applied for the generation of relevant VID models, which in turn, could be used to perform the Prestack Depth Migration (PreSDM) procedures. The application of procedures taking advantage of independent geophysical and geological data enabled researchers to control the generation process of the spatial VID model in the areas without wells. The analyses aimed to verify the correctness of VID model evaluation and its influence on the quality of seismic imaging in the area of the Carpathian Overthrust. Precisely, the influence was tested of such non-standard generation procedure of seismic velocity fields, not only on the PreSDM results but also on the geological interpretation of both the Rączyna and the Jodłówka gas deposits. The latter aspect of the presented results seems to be crucial to the effectiveness of petroleum exploration in the transition zone between the Carpathian Orogen and the Carpathian Foredeep. Full article

The extraction of impacted third molars is one of the most common dental operations. When the impacted third molar is extracted, the operation plan is generally different because of the different impacted positions of the tooth. Therefore, judging the impacted type of the third molar is the basis of the third molar extraction operation. At present, oral health professionals usually analyze panoramic radiographs to determine the types of impacted third molars, but the diagnosis is easily affected by oral health professionals’ subjective consciousnesses. Computer vision technology can help doctors analyze medical images faster and more accurately, so it is very desirable to use computer vision to detect and classify the impacted third molars. Based on the panoramic radiographs of the School of Stomatology, Lanzhou University, this paper establishes an object detection dataset containing six types of impacted third molars. On the basis of this dataset, the lightweight third molar impacted detection and classification model is studied in this paper. This study introduces the method of knowledge distillation on the basis of YOLOv5s and uses YOLOv5x as the teacher’s model to guide YOLOv5s, which not only ensures the light weight of the model but also improves the accuracy of the model. Finally, the YOLOv5s-x model is obtained. The experimental results show that the introduction of knowledge distillation effectively improves the accuracy of the model while ensuring its light weight, the mAP of YOLOv5s-x is increased by 2.9% compared with the original model, and the amount of parameters and calculations is also reduced to a certain extent. Compared with mainstream object detection networks, including YOLOv8, YOLOv5s-x also has certain advantages, which can provide oral health professionals with better impacted third molar detection and classification services. Full article

This paper proposes a novel Sea Drift Trajectory Prediction method based on the Quantum Convolutional Long Short-Term Memory (QCNN-LSTM) model. Accurately predicting sea drift trajectories is a challenging task, as they are influenced by various complex factors, such as ocean currents, wind speed, and wave morphology. Therefore, in a complex marine environment, there is a need for more applicable and computationally advanced prediction methods. Our approach combines quantized convolutional neural networks with Long Short-Term Memory networks, utilizing two different input types of prediction to enhance the network’s applicability. By incorporating quantization techniques, we improve the computational power and accuracy of the trajectory prediction. We evaluate our method using sea drift datasets and AUV drift trajectory datasets, comparing it with other commonly used traditional methods. The experimental results demonstrate significant improvements in accuracy and robustness achieved by our proposed Quantum Convolutional Long Short-Term Memory model. Regardless of the input mode employed, the accuracy consistently surpasses 98%. In conclusion, our research provides a new approach for sea drift trajectory prediction, enhancing prediction accuracy and providing valuable insights for marine environmental management and related decision-making. Future research can further explore and optimize this model to have a greater impact on marine prediction and applications. Full article

The surrounding rock during a coal mine excavation is prone to significant engineering disasters such as considerable deformation and rock bursts. Pressure release can improve the stress field of a deep rock mass and prevent the occurrence of dangers such as roadway collapse and coal and gas outbursts. This paper uses the ANSYS 19.0/LS-DYNA finite element software to simulate the crush area and fracture zone of a detonation charge with different diameters under in situ stress. The stability of the surrounding rock was analyzed based on the impact stress and velocity, and was verified by field tests. The research results show that the blasting load primarily affects the damaged area near the borehole, while the in situ stress affects far-field crack propagation. The crack propagates in the direction of high surrounding rock pressure. When the uncoupling index is 1.5, the impact pressure of a 60 mm diameter cartridge is eight times that of a 20 mm diameter cartridge. The impact speed can reach two times that of the 20 mm diameter cartridge. The high-energy event at the roof is transferred to the front of the working face, the distribution is no longer concentrated, and a better pressure-relief blasting effect is achieved. The research results can help guide the prevention and control measures of rock bursts and other mining disasters. Full article

In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim of preserving significant properties from the original data. Many dimensionality reduction algorithms exist, and nonlinear approaches such as the t-SNE (t-Distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection) have gained popularity in the field of information visualization. In this paper, we introduce a simple yet powerful manipulation for vector datasets that modifies their values based on weight frequencies. This technique significantly improves the results of the dimensionality reduction algorithms across various scenarios. To demonstrate the efficacy of our methodology, we conduct an analysis on a collection of well-known labeled datasets. The results demonstrate improved clustering performance when attempting to classify the data in the reduced space. Our proposal presents a comprehensive and adaptable approach to enhance the outcomes of dimensionality reduction for visual data exploration. Full article

Active optics is a key technology in ground-based large-aperture telescopes. The active correction of the surface shape of the primary mirror is used to reduce the surface shape error and improve the imaging quality. At present, the structure of the active optics support system is not standardized. Therefore, to ensure the imaging quality of a telescope using a 4m SiC (silicon carbide) primary mirror, this article designed an active support system for the primary mirror and comprehensively evaluated the performance of the system. The system used pneumatic actuators to correct the surface shape of the primary mirror and a six-hardpoint positioning mechanism to correct the pose of the primary mirror. A method for compensating for the force on the hardpoints that causes protrusions and dents on the primary mirror surface was proposed, which effectively improved the accuracy of the primary mirror surface. The bending-mode method was used to determine the correction force. To achieve better results in the surface shape correction based on the bending mode, the relationship between the order of the bending modes used in the correction and the correction effect was studied, enabling the system to achieve a higher surface shape accuracy with a smaller correction force. Finally, the performance of the system was evaluated under various conditions, such as under gravity, thermal load, and wind load. The results indicated that the system had good correction effects on the deformation of the primary mirror under various operating conditions and could meet the requirements of optical design for surface accuracy. In conclusion, this study not only verified the application of active optics technology based on the bending mode in large-aperture SiC mirrors, but also improved on the relevant theoretical research on active optics. Full article

An approach based on an artificial neural network (ANN) for the prediction of NOx emissions from underground load–haul–dumping (LHD) vehicles powered by diesel engines is proposed. A Feed-Forward Neural Network, the Multi-Layer Perceptron (MLP), is used to establish a nonlinear relationship between input and output layers. The predicted values of NOx emissions have less than 15% error compared to the real values measured by the LHD onboard monitoring system by the standard sensor. This is considered quite good efficiency for dynamic behaviour prediction of extremely complex systems. The achieved accuracy of NOx prediction allows the application of the ANN-based “soft sensor” in environmental impact estimation and ventilation system demand planning, which depends on the number of working LHDs in the underground mine. The proposed solution to model NOx concentrations from mining machines will help to provide a better understanding of the atmosphere of the working environment and will also contribute to improving the safety of underground crews. Full article

This paper presents the design and testing of an ultra-low-noise transimpedance amplifier (TIA) for low-frequency noise measurements on low-impedance (below 1 kΩ) devices, such as advanced IR photodetectors. When dealing with low-impedance devices, the main source of background noise in transimpedance amplifiers comes from the equivalent input voltage noise of the operational amplifier, which is used in a shunt–shunt configuration to obtain a transimpedance stage. In our design, we employ a hybrid operational amplifier in which an input front end based on ultra-low-noise discrete JFET devices is used to minimize this noise contribution. When using IF3602 JFETs for the input stage, the equivalent voltage noise of the hybrid operational amplifier can be as low as 4 nV/√Hz, 2 nV/√Hz, and 0.9 nV/√Hz at 1 Hz, 10 Hz, and 1 kHz, respectively. When testing the current noise of an ideal 1 kΩ resistor, these values correspond to a current noise contribution of the same order as or below that of the thermal noise of the resistor. Therefore, in cases in which the current flicker noise is dominant, i.e., much higher than the thermal noise, the noise contribution from the transimpedance amplifier can be neglected in most cases of interest. Test measurements on advanced low-impedance photodetectors are also reported to demonstrate the effectiveness of our proposed approach for directly measuring low-frequency current noise in biased low-impedance electronic devices. Full article