TY - JOUR AU - Kim, Saewhan AU - Horvath, Laszlo AU - Lee, Soohyung AU - Lee, Sangwook TI - Measurement and Analysis of Last-Mile Parcel Delivery Truck Vibration Levels in Korea JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 8 SP - 3245 SN - 2076-3417 DO - 10.3390/app14083245 UR - https://m2.mtmt.hu/api/publication/34789033 ID - 34789033 AB - South Korea has one of the largest e-commerce markets in the world. The last-mile delivery segment of e-commerce often causes critical damage to products in protective packages. Despite the rapid growth of the e-commerce market in Korea, the last-mile distribution environment has not yet been thoroughly investigated. The main aim of this study was to provide an understanding of the vibration levels that were measured from various parcel delivery routes within Seoul, Korea, using common types of parcel delivery trucks. Vibration levels of ten delivery trucks were measured and analyzed in terms of power spectral densities (PSDs) and presented as PSD spectra. The last-mile delivery vehicle vibration levels in Korea were found to be consistently lower (in the 1 to 200 Hz frequency range) than those recommended by international standards and lower than the vibration levels of parcel delivery vehicles in the U.S. and Hungary. The results also revealed that the highest intensity peak of the PSD spectrum for Korea was located in the lower frequency range (1.5 to 2 Hz) compared to the ISTA 3A pickup and delivery test profile (3 to 4 Hz) and the test profile recommended for Hungary (13 to 16 Hz). A smoothed composite spectrum was also provided to support Korean packaging engineers in optimizing their packages by simulating proper last-mile truck delivery vibration levels in lab conditions. LA - English DB - MTMT ER - TY - JOUR AU - Li, Xiang AU - Li, Gang AU - Zhang, Zhiqiang TI - Research on Obstacle Avoidance Replanning and Trajectory Tracking Control Driverless Ferry Vehicles JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 8 SP - 3216 SN - 2076-3417 DO - 10.3390/app14083216 UR - https://m2.mtmt.hu/api/publication/34788839 ID - 34788839 AB - This study aimed to solve the problem that is the frequent switching between the acceleration and braking modes of the driverless ferry vehicle, affecting the comfort and stability of speed control. The driverless ferry vehicle encounters unknown obstacles on the road that affect the normal planning and tracking control of the ferry vehicle and finally lead to the problem that the driverless ferry vehicle cannot drive normally. First of all, in the longitudinal control, the fuzzy PID control algorithm was utilized to produce the fuzzy PID acceleration controller by taking into account the difference between the actual and expected speeds and choosing the triangular membership function. According to the relationship between the brake oil pressure and brake torque, the brake controller was designed. The acceleration/braking switching module with acceleration tolerance zone was added to the longitudinal controller, and the acceleration/braking mode-switching controller was designed. Secondly, in the lateral control, the tire cornering stiffness was analyzed, an MPC controller with a planning module was designed, and a lateral motion controller with an obstacle avoidance replanning function was proposed. Finally, according to the prediction time domain of different planning modules corresponding to different speeds, a coordinated control strategy of horizontal and longitudinal motion was proposed by using a real-time speed adjustment planning module to predict the time domain. Through the joint simulation analysis of MATLAB and CarSim, the results show that the driving stability of the ferry vehicle was significantly improved, and the longitudinal speed error of the ferry vehicle was reduced by 43.59%. The ferry’s avoidance of obstacles and tracking of reference trajectories were significantly improved, so that the tracking error can be reduced by 61.11%. LA - English DB - MTMT ER - TY - JOUR AU - Wang, Siyu AU - Jia, Jie TI - Study on Fatigue Life of PC Composite Box Girder Bridge with Corrugated Steel Webs under the Combined Action of Temperature and Static Wind Loads JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 8 SP - 3165 SN - 2076-3417 DO - 10.3390/app14083165 UR - https://m2.mtmt.hu/api/publication/34786394 ID - 34786394 AB - The large-span bridge is highly sensitive to temperature and wind loads. Therefore, it is essential to study the bridge’s fatigue life under the combined effects of temperature and static wind loads. This study focuses on the main bridge of Qiao Jia-fan 2# on the Yinkun Expressway (G85), with a span of 250 m and a configuration of a PC composite box girder bridge with corrugated steel webs. Firstly, on-site temperature and wind direction measurements with wind speed were conducted at the bridge site. Origin 2022 software is used to make mathematical statistics on the data, the representative values of atmospheric temperature difference between day and night and the basic wind speeds are calculated. Secondly, based on the basic wind speed in the most unfavorable wind direction, the static three-component force coefficients of bridge at different angles of attack are calculated by FLUENT 2022 R1 software. By comparison, the most unfavorable wind angle of attack, wind direction and wind load value of Qiao Jia-fan 2# Bridge are obtained. Finally, the finite element software MIDAS/FEA NX 2022 is used to analyze the fatigue life of the main bridge of the Qiao Jia-fan 2# Bridge. The analysis results show that the representative value of the temperature difference between day and night in the area where PC composite box girder bridge with corrugated steel webs is located is 22 °C, the most unfavorable wind direction is NNE wind direction, and the most unfavorable wind attack angle is 3° wind attack angle. It is found that the maximum stress of concrete and corrugated steel webs appears near the 0# block, and the life of corrugated steel webs is far greater than that of concrete. LA - English DB - MTMT ER - TY - JOUR AU - Zhao, He AU - Zhang, Wei TI - Last Glacial Maximum Climate and Glacial Scale Affected by the Monsoon Inferred from Reconstructing the Tianchi Area, Changbai Mountains, Eastern China JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 3019 SN - 2076-3417 DO - 10.3390/app14073019 UR - https://m2.mtmt.hu/api/publication/34787554 ID - 34787554 AB - There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area’s paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km2 and the glacial volume was ~9.94 km3; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today’s, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. LA - English DB - MTMT ER - TY - JOUR AU - Cai, Hu AU - Wan, Jiafu AU - Chen, Baotong TI - Digital Twin-Driven Multi-Factor Production Capacity Prediction for Discrete Manufacturing Workshop JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 3119 SN - 2076-3417 DO - 10.3390/app14073119 UR - https://m2.mtmt.hu/api/publication/34784531 ID - 34784531 AB - Traditional capacity forecasting algorithms lack effective data interaction, leading to a disconnection between the actual plan and production. This paper discusses the multi-factor model based on a discrete manufacturing workshop and proposes a digital twin-driven discrete manufacturing workshop capacity prediction method. Firstly, this paper gives a system framework for production capacity prediction in discrete manufacturing workshops based on digital twins. Then, a mathematical model is described for discrete manufacturing workshop production capacity under multiple disturbance factors. Furthermore, an innovative production capacity prediction method, using the “digital twin + Long-Short-Term Memory Network (LSTM) algorithm”, is presented. Finally, a discrete manufacturing workshop twin platform is deployed using a commemorative disk custom production line as the prototype platform. The verification shows that the proposed method can achieve a prediction accuracy rate of 91.8% for production line capacity. By integrating the optimization feedback function of the digital twin system into the production process control, this paper enables an accurate perception of the current state and future changes in the production system, effectively evaluating the production capacity and delivery date of discrete manufacturing workshops. LA - English DB - MTMT ER - TY - JOUR AU - Hussain, Syed Safdar AU - Zaidi, Syed Sajjad Haider TI - AdaBoost Ensemble Approach with Weak Classifiers for Gear Fault Diagnosis and Prognosis in DC Motors JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 3105 SN - 2076-3417 DO - 10.3390/app14073105 UR - https://m2.mtmt.hu/api/publication/34784195 ID - 34784195 AB - This study introduces a novel predictive methodology for diagnosing and predicting gear problems in DC motors. Leveraging AdaBoost with weak classifiers and regressors, the diagnostic aspect categorizes the machine’s current operational state by analyzing time–frequency features extracted from motor current signals. AdaBoost classifiers are employed as weak learners to effectively identify fault severity conditions. Meanwhile, the prognostic aspect utilizes AdaBoost regressors, also acting as weak learners trained on the same features, to predict the machine’s future state and estimate its remaining useful life. A key contribution of this approach is its ability to address the challenge of limited historical data for electrical equipment by optimizing AdaBoost parameters with minimal data. Experimental validation is conducted using a dedicated setup to collect comprehensive data. Through illustrative examples using experimental data, the efficacy of this method in identifying malfunctions and precisely forecasting the remaining lifespan of DC motors is demonstrated. LA - English DB - MTMT ER - TY - JOUR AU - Wang, Shubin AU - Chen, Yuanyuan AU - Yi, Zhang TI - A Multi-Scale Attention Fusion Network for Retinal Vessel Segmentation JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 2955 SN - 2076-3417 DO - 10.3390/app14072955 UR - https://m2.mtmt.hu/api/publication/34766390 ID - 34766390 AB - The structure and function of retinal vessels play a crucial role in diagnosing and treating various ocular and systemic diseases. Therefore, the accurate segmentation of retinal vessels is of paramount importance to assist a clinical diagnosis. U-Net has been highly praised for its outstanding performance in the field of medical image segmentation. However, with the increase in network depth, multiple pooling operations may lead to the problem of crucial information loss. Additionally, handling the insufficient processing of local context features caused by skip connections can affect the accurate segmentation of retinal vessels. To address these problems, we proposed a novel model for retinal vessel segmentation. The proposed model is implemented based on the U-Net architecture, with the addition of two blocks, namely, an MsFE block and MsAF block, between the encoder and decoder at each layer of the U-Net backbone. The MsFE block extracts low-level features from different scales, while the MsAF block performs feature fusion across various scales. Finally, the output of the MsAF block replaces the skip connection in the U-Net backbone. Experimental evaluations on the DRIVE dataset, CHASE_DB1 dataset, and STARE dataset demonstrated that MsAF-UNet exhibited excellent segmentation performance compared with the state-of-the-art methods. LA - English DB - MTMT ER - TY - JOUR AU - Kolanowski, Wojciech TI - Perspective of Using Apple Processing Waste for the Production of Edible Oil with Health-Promoting Properties JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 2932 SN - 2076-3417 DO - 10.3390/app14072932 UR - https://m2.mtmt.hu/api/publication/34763556 ID - 34763556 AB - (1) Background: The effective management of waste and by-products generated in the food industry helps development and implementation of ranges of health-promoting products. The manufacturing of apple juice and cider results in the generation of large quantities of apple pomace. (2) Methods: This paper outlines the concept of a technological process for industrial-scale production of edible oil with a health-promoting fatty acids profile using dried apple pomace as a raw material. (3) Results: Described approach allows for innovative and profitable industrial-scale utilization of the pomace generated from apple juice production. This paper presents a new technological line for apple seed separation intended for oil pressing. (4) Conclusions: The new technological approach could increase the production of apple seed oil. Because of the growing needs in managing post-production waste and by-products, apple seed oil produced from apple pomace on an industrial scale may become a new, attractive product in the functional food market. The fatty acids profile of apple seed oil is high in polyunsaturated fatty acids and can beneficially influence health. The technology outlined here is in the conceptual phase and requires further research. LA - English DB - MTMT ER - TY - JOUR AU - Besharati Moghaddam, Fatemeh AU - Lopez, Angel J. AU - De Vuyst, Stijn AU - Gautama, Sidharta TI - Natural Language Processing in Knowledge-Based Support for Operator Assistance JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 2766 SN - 2076-3417 DO - 10.3390/app14072766 UR - https://m2.mtmt.hu/api/publication/34763204 ID - 34763204 AB - Manufacturing industry faces increasing complexity in the performance of assembly tasks due to escalating demand for complex products with a greater number of variations. Operators require robust assistance systems to enhance productivity, efficiency, and safety. However, existing support services often fall short when operators encounter unstructured open questions and incomplete sentences due to primarily relying on procedural digital work instructions. This draws attention to the need for practical application of natural language processing (NLP) techniques. This study addresses these challenges by introducing a domain-specific dataset tailored to assembly tasks, capturing unique language patterns and linguistic characteristics. We explore strategies to process declarative and imperative sentences, including incomplete ones, effectively. Thorough evaluation of three pre-trained NLP libraries—NLTK, SPACY, and Stanford—is performed to assess their effectiveness in handling assembly-related concepts and ability to address the domain’s distinctive challenges. Our findings demonstrate the efficient performance of these open-source NLP libraries in accurately handling assembly-related concepts. By providing valuable insights, our research contributes to developing intelligent operator assistance systems, bridging the gap between NLP techniques and the assembly domain within manufacturing industry. LA - English DB - MTMT ER - TY - JOUR AU - Sánchez-Guzmán, Alejandra AU - Bedolla-Rivera, Héctor Iván AU - Conde-Barajas, Eloy AU - Negrete-Rodríguez, María de la Luz Xochilt AU - Lastiri-Hernández, Marcos Alfonso AU - Gámez-Vázquez, Francisco Paúl AU - Álvarez-Bernal, Dioselina TI - Corn Cropping Systems in Agricultural Soils from the Bajio Region of Guanajuato: Soil Quality Indexes (SQIs) JF - APPLIED SCIENCES-BASEL J2 - APPL SCI-BASEL VL - 14 PY - 2024 IS - 7 SP - 2858 SN - 2076-3417 DO - 10.3390/app14072858 UR - https://m2.mtmt.hu/api/publication/34763072 ID - 34763072 AB - Agriculture is a sector of great importance for Mexico’s economy, generating employment and contributing significantly to the country’s gross domestic product. The Bajio stands out as one of the most productive agricultural regions in Mexico. However, intensive agricultural practices in this area have caused a progressive deterioration and loss of soil fertility. This study focused on evaluating the quality of soils used for agriculture in the Bajio region of the State of Guanajuato, Mexico. This evaluation, utilised soil quality indexes (SQIs) based on a total of 27 physicochemical, biological and enzymatic indicators. These indicators were selected by means of a principal component analysis (PCA), which allowed for the identification of a minimum set of data. The SQIs developed in this study categorised soils into different quality levels, ranging from low to high, mainly based on the values observed in the biological indicators (SMR and qCO2), which comprised the established SQIs. The inclusion of these biological indicators provides the developed SQIs with greater sensitivity to detect minor disturbances in agricultural soils due to human activity, compared with SQIs consisting only of physicochemical indicators. The developed SQIs can be used to ensure high-quality food production in soils used for corn cultivation under similar conditions, both nationally and internationally. LA - English DB - MTMT ER -