Meniscal tears, a prevalent orthopedic condition caused by abrupt knee movements, excessive load, or injury, require an accurate diagnosis for effective treatment. This study investigates the vision transformer (ViT) ...
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Consolidating the Internet of Things (IoT) and software Defined Networks (SDN) has been a great concern among researchers. In IoT, Wireless Sensor Network (WSN) is important communication component. Due to the large v...
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The global elderly population is projected to double by 2050, creating challenges in mobility, social isolation, and cognitive decline. Socially Assistive Robots (SARs) offer a promising solution, yet gaps remain in i...
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In this study,the pure erosion behaviour of pure iron and its erosion-corrosion behaviour under different anodic polarization currents were investigated in various cathodic reactions(oxygen reduction,hydrogen ion redu...
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In this study,the pure erosion behaviour of pure iron and its erosion-corrosion behaviour under different anodic polarization currents were investigated in various cathodic reactions(oxygen reduction,hydrogen ion reduction,and water reduction)using a cylindrical stirring *** corrosion-enhanced erosion(C-E)rates were determined for each *** results revealed that pure iron displayed similar pure erosion behaviour across all three cathodic *** the cathodic reactions involve hydrogen ion reduction or water reduction,the erosion-corrosion of pure iron manifested as uniform damage,with the reduction in hardness being the main cause of the C-E in this ***,in the case of oxy-gen reduction reaction as the cathodic reaction,the erosion-corrosion presented as pitting damage,with the reduction in hardness resulting from localized concentration of anodic current and the formation of easily worn protruding flaky iron structures at the edges of the pits as the main mechanism of the ***,linear and exponential relationships were found between the C-E rate and the anodic current density for uniform damage and pitting damage,***,the concept of surface equivalent hardness was proposed,along with the establishment of a mathematical model for surface equivalent hardness based on the relationships between the C-E rate and the anodic current *** the surface equivalent hardness enables the evaluation of the erosion rate on material surfaces considering the coupled effect.
Corrosion poses a major threat to the safety of transportation ***,it is crucial to have an in-depth understanding of corrosion mechanisms in pipeline steels for the effective management of pipeline *** research on co...
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Corrosion poses a major threat to the safety of transportation ***,it is crucial to have an in-depth understanding of corrosion mechanisms in pipeline steels for the effective management of pipeline *** research on corrosion mechanisms relies on the use of efficient and reliable corrosion monitoring and analysis *** advancements in corrosion monitoring techniques specifically designed for the localized corrosion monitoring were aimed to be introduced,and a comprehensive overview of recent progress in understanding the localized corrosion mechanisms in pipeline steels was *** on the different corrosive environments encountered,the localized corrosion issues inside pipelines are classified into two categories:localized corrosion primarily influenced by electrochemical processes and localized corrosion controlled by both electrochemical and mechanical ***,a thorough analysis of the synergistic effects between micro-cell and macro-cell currents,as well as the interplay of mechanics and electrochemistry is ***,recommendations for future research on the mechanisms of internal localized corrosion in pipelines are provided.
Category-level pose estimation methods have received widespread attention as they can be generalized to intra-class unseen objects. Although RGB-D-based category-level methods have made significant progress, reliance ...
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Diabetes mellitus (DM) is a chronic metabolic disorder affecting millions worldwide, necessitating accurate diagnosis and effective treatment strategies. Traditional diagnostic approaches, including fasting blood gluc...
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ISBN:
(数字)9798331510886
ISBN:
(纸本)9798331510893
Diabetes mellitus (DM) is a chronic metabolic disorder affecting millions worldwide, necessitating accurate diagnosis and effective treatment strategies. Traditional diagnostic approaches, including fasting blood glucose (FBG) and hemoglobin A1c (HbA1c) tests, have limitations in predicting disease progression and addressing complex drug interactions. In this study, machine learning (ML) and deep learning (DL) models were utilized to enhance both diabetes classification and drug interaction risk assessment. Specifically, the Pima Indian Diabetes Dataset was employed for diabetes diagnosis, utilizing eight clinical features selected through Mutual Information (MI). To address class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied. Among machine learning models, Random Forest (RF) achieved the highest accuracy of 98.7%, while LSTM networks performed best among deep learning models, reaching 97.2% accuracy. In the drug interaction risk classification task, a custom dataset based on clinical guidelines from the Turkish Endocrinology Society was used. This dataset, comprising 109 records, details pairwise drug interactions, pharmacokinetic mechanisms, and risk levels (moderate or high). An ensemble model combining Random Forest and Decision Tree classifiers, utilizing a weighted voting mechanism, achieved 100% accuracy. However, the small dataset size underscores the need for further validation with larger, more diverse datasets. Comparative analysis demonstrated that ensemble learning and deep learning models outperform conventional classification techniques, reinforcing their potential in clinical decision support systems. Future work will focus on expanding the dataset, integrating additional patient-specific parameters, and optimizing model generalizability for real-world applications.
Good growth of tomato at the early growing stages is the key to final yield formation,for which water(W)and nitrogen(N)applications are two necessary *** this study,two irrigating systems(W1,W2)and three N application...
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Good growth of tomato at the early growing stages is the key to final yield formation,for which water(W)and nitrogen(N)applications are two necessary *** this study,two irrigating systems(W1,W2)and three N applications(N1,N2,N3)were interacted(W×N)to plant the cherry tomato variety‘‘Jinling Meiyu’’in greenhouse.W1(reduced irrigation)and W2(normal irrigation)had a 7:9 irrigated ratio based on former research.N1,N2,and N3 were set at 100%,80%,and 60%normal N application,*** tomato plant height(PH),stem circumference(SC),number of leaves(NL),number of first order fruits(NF),the single fruit weight(SFW),contents of fruit Vitamin C(VC)and soluble sugar(SS),fresh weights of root(RW),leaf(LW),and plant stem(PSW),as well as leaf chlorophyll fluorescence value(SPAD),temperature(T),humidity(RH),and nitrogen content(N)were investigated at the first flowering and fruiting *** results showed that W×N had significant impacts on early plant growth and fruit quality of tomato.W2N2 obviously received the largest values of tomato PH(152.5 cm),SC(4.1 cm),NF(11 fruits/plant),and LW(45.0 g/plant),but obtained the lowest VC(9.71 mg/kg)and SS(2.40%).However,W1N3 had the largest values of leaf RH(56.9%),N contents(14.23 mg/g),and VC(16.29 mg/kg),with NF also at 11.0 fruits/plant.W2N1 significantly had the highest RW(14.4 g/plant),PSW(71.8 g/plant),and SFW(21.3 g/fruit).W2N3,W1N1,and W1N2 obtained the most NL(103.7 pieces/plant),SS(4.06%),and leaf SPAD(36.85),*** correlation analysis results showed PH negatively significantly correlated with NF(p<0.05).The leaf SPAD positively significantly correlated with PH(p<0.05)and RH(p<0.01),but negatively significantly correlated with SC(p<0.05)and T(p<0.01).Moreover,leaf N content also had a positive significant correlation with PH(p<0.05),and an extremely positive significant correlation with RH and SPAD(p<0.01).However,it negatively significantly correlated with SC(p<0.01)and T(p<0.05).Significantly,VC ha
A multi-objective optimization problem involves optimizing two or more conflicting objectives simultaneously. This type of problem arises in many scientific and industrial areas and it is classified as NP-Hard. Networ...
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A multi-objective optimization problem involves optimizing two or more conflicting objectives simultaneously. This type of problem arises in many scientific and industrial areas and it is classified as NP-Hard. Network routing optimization with multiple objectives falls into this category. In the context of 6G networks, solving this problem will become even more challenging due to the exponential growth of Internet of Things devices and the high quality of service requirements. Finding good quality solutions for large-scale networks will be increasingly difficult. In this paper, we introduce a quantum-inspired routing optimization scheme in which noisy-intermediate scale quantum computers (NISQ) can be used to solve the Multi-Objective Routing Problem (MORP). We evaluate the application of the proposed scheme in detail by first developing the mathematical formulas for both single-objective and multi-objective routing and mapping the problem onto gate-based models by using the quadratic unconstrained binary optimization (QUBO) approach. To validate the proposed scheme, we use the quantum approximate optimization algorithm (QAOA), the go-to approach for solving combinatorial optimization problems that are classically intractable. For the simulation, we use the IBM-Qasm simulator and Qiskit framework. Additionally, we use the Chernoff Bound as a standard technique to estimate the sample complexity of QAOA. Finally, we provide a detailed numerical and theoretical analysis of the proposed scheme, including its time complexity, resource requirements, and the challenges associated with it. Our results demonstrate that the proposed approach operates with a time complexity of O(E2) per iteration in both single and multi-objective scenarios, with an overall runtime of (niteration + nCB) ⋅ O(E2) influenced by the sampling overhead, significantly outperforming Dijkstra's algorithm in the multi-objective case, where the complexity incr
A novel numerical approach, leveraging the 3D time domain Rankine panel method, has been introduced to simulate ship motions while accounting for the effects of ship wave. This method treats ship wave as steady flow, ...
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A novel numerical approach, leveraging the 3D time domain Rankine panel method, has been introduced to simulate ship motions while accounting for the effects of ship wave. This method treats ship wave as steady flow, enabling a more accurate representation of physical phenomena. The underlying numerical formulation used to solve the ship wave potential is comprehensively derived, establishing the unsteady disturbance potential's boundary value problem and incorporating the effects of steady motion. Wave forces and motion responses of various ship forms were computed and compared with experimental data and results from other numerical techniques. The findings reveal that calculations based on uniform stream exhibit significantly larger errors than those considering double body flow or ship wave. For the Wigley I and S175 models, the discrepancies between double body flow and ship wave predictions are relatively minor, with ship wave calculations demonstrating slightly higher accuracy. In contrast, for the intricate KRISO Container Ship (KCS) model, where ship wave is more pronounced, the error margin for ship wave calculations relative to experimental results remains within 21.9%, while errors for double body flow calculations can reach up to 50.2%. This highlights the superior accuracy of ship wave-based calculations for the KCS model. Overall, the proposed method effectively captures the influence of steady flow and demonstrates significant advantages in computing pronounced ship wave generated during realistic ship motion.
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