Navigated Research Articles

Evaluation of changes in fixed flexion deformity following medial unicompartmental knee arthroplasty.

While residual fixed flexion deformity (FFD) in unicompartmental knee arthroplasty (UKA) has been associated with worse functional outcomes, limited evidence exists regarding FFD changes. The objective of this study was to quantify FFD changes in patients with medial unicompartmental knee arthritis undergoing UKA, and investigate any correlation with clinical outcomes. This study included 136 patients undergoing robotic arm-assisted medial UKA between January 2018 and December 2022. The study included 75 males (55.1%) and 61 (44.9%) females, with a mean age of 67.1 years (45 to 90). Patients were divided into three study groups based on the degree of preoperative FFD: ≤ 5°, 5° to ≤ 10°, and > 10°. Intraoperative optical motion capture technology was used to assess pre- and postoperative FFD. Clinical FFD was measured pre- and postoperatively at six weeks and one year following surgery. Preoperative and one-year postoperative Oxford Knee Scores (OKS) were collected. Overall, the median preoperative navigated (NAV) FFD measured 6.0° (IQR 3.1 to 8), while the median postoperative NAV FFD was 3.0° (IQR 1° to 4.4°), representing a mean correction of 49.2%. The median preoperative clinical FFD was 5° (IQR 0° to 9.75°) for the entire cohort, which decreased to 3.0° (IQR 0° to 5°) and 2° (IQR 0° to 3°) at six weeks and one year postoperatively, respectively. A statistically significant improvement in PROMs compared with baseline was evident in all groups (p < 0.001). Regression analyses showed that participants who experienced a larger FFD correction, showed greater improvement in PROMs (β = 0.609, p = 0.049; 95% CI 0.002 to 1.216). This study found that UKA was associated with an approximately 50% improvement in preoperative FFD across all three examined groups. Participants with greater correction of FFD also demonstrated larger OKS gains. These findings could prove a useful augment to clinical decision-making regarding candidacy for UKA and anticipated improvements in FFD.

Spatiotemporal Point–Trace Matching Based on Multi-Dimensional Feature Fuzzy Similarity Model

Identifying ships is essential for maritime situational awareness. Automatic identification system (AIS) data and remote sensing (RS) images provide information on ship movement and properties from different perspectives. This study develops an efficient spatiotemporal association approach that combines AIS data and RS images for point–track association. Ship detection and feature extraction from the RS images are performed using deep learning. The detected image characteristics and neighboring AIS data are compared using a multi-dimensional feature similarity model that considers similarities in space, time, course, and attributes. An efficient spatial–temporal association analysis of ships in RS images and AIS data is achieved using the interval type-2 fuzzy system (IT2FS) method. Finally, optical images with different resolutions and AIS records near the waters of Yokosuka Port and Kure are collected to test the proposed model. The results show that compared with the multi-factor fuzzy comprehensive decision-making method, the proposed method can achieve the best performance (F1 scores of 0.7302 and 0.9189, respectively, on GF1 and GF2 images) while maintaining a specific efficiency. This work can realize ship positioning and monitoring based on multi-source data and enhance maritime situational awareness.

Accuracy verification of the 2D spectral AIS method by the hull monitoring data

Accuracy validation of the 2D spectral AIS method (AIS method using two-dimensional wave spectrum; 2D-AIS method) using hull monitoring data of a large ore carrier is discussed. The AIS method predicts the response of actual ships using AIS-based ship position data, hindcast wave data, and response characteristics data. The conventional AIS method uses representative parameters(H, T, θ) from wave spectrum modeling. The modeling involves many uncertainties. By using the 2D wave spectrum as it is, the effect of uncertainties associated with wave spectrum modeling is investigated. Compared to the analysis of the monitoring data conducted in this study, it was found that the 2D-AIS method improves the accuracy to about 15 %, while the conventional AIS method shows an error of up to about 35 % compared to the actual measurements in the long-term maximum expected values. This enhancement is attributed to the inability of the modeled wave spectrum to accurately represent the two-peak wave spectrum observed in extreme sea states, leading to a deficiency in reproducing wave frequency components corresponding to peak frequencies of the response. The findings underscore the effectiveness of the 2D-AIS method in refining long-term hull stress estimations, thus offering valuable insights for enhancing the safety and performance of hull structures.

Ship visual trajectory exploitation via an ensemble instance segmentation framework

Maritime traffic safety is of utmost importance in the shipping industry. It is common to avoid potential traffic accident via the support of varied kinematic maritime data (e.g., ship position, ship speed). The study aims to fulfill maritime traffic safety enhancement by extracting multiple ship trajectories from maritime video data. The proposed framework is implemented with three steps. Firstly, the framework obtains initial ship imaging positions by proposing an ensemble YOLOX (You Only Look Once X) with CenterNet model. Secondly, ship contours from each maritime frame are explored with the deep snake module. Thirdly, consecutive ship imaging trajectory is identified with an enhanced Bytetrack multi-ship target tracking algorithm. Experimental results demonstrate that our model outperforms other ship trajectory extraction-like models considering that the identification F-Score (IDF1), IDP (identification Precision), IDR (identification recall), and MOTA (multi-object tracking accuracy) for our proposed framework were 0.965, 0.995, 0.933, and 0.925, respectively. The research findings can help ship crew better aware on-site traffic situations, and thus make optimal ship maneuvering operations for the purpose of enhancing maritime traffic system safety and sustainability.

E-Textbooks as a Teaching Aid at a University of Technology in South Africa: A Cultural-Historical Activity Theory Analysis

The past two years saw a rapid proliferation of information and communication technologies (ICTs) in higher education. Digital technologies and environments offer many affordances. New digital literacy practices in universities have implications for teaching and learning. E-textbooks, in particular, act as mediating tools that can facilitate teaching and learning through developing students’ understandings of scientific concepts. This paper positions e-textbooks as mediators of learning, rather than merely objects of learning. There is thus a need to understand the mediating role of e-textbooks that lecturers draw on in their teaching. While much research was conducted on students’ use of e-textbooks, relatively little was conducted on lecturers’ use of e-textbooks in engineering education. The current study aimed to answer the following research question: What are lecturers’ perspectives on the use of e-textbooks to facilitate learning in engineering? To address this question, data were collected through five individual interviews conducted with engineering lecturers working in the Extended Curriculum Programme (ECP) of first-year students from three engineering departments (chemical engineering, mechanical engineering, and nautical science) at a university of technology in South Africa. The data were analysed using thematic content analysis with the help of ATLAS.ti. Data analysis was guided by a theoretical framework that drew on the cultural-historical activity theory (CHAT). In this study, the focus was on e-textbooks as pedagogical tools within engineering teaching and learning. The findings provide insight into how lecturers incorporate e-textbooks into their teaching, but also reveal the extent to which new digital literacy reading practices remain unfamiliar to engineering lecturers. CHAT enabled the identification of a critical insight, namely, the tension between mediation and division of labour. This highlights important aspects of the discourse surrounding seamless technology integration in higher education. The discussion points to the need for an expansive transformation regarding the use of e-textbooks as important mediating tools for teaching and learning.

Detection range of a passing submerged emitter of sound in ambient noisea).

An underwater acoustic detection problem is studied in which the ambient noise present at a receiver is calculated, given information describing environmental conditions, including windspeed, and the positions of nearby ships which act as sources of background noise. The signal, whose detection is sought, is narrowband and transmitted from a source that passes by the receiver along a straight track. Cumulative Probability of Detection (CPoD) is calculated along a series of tracks with increasing closest-point-of-approach distances to the receiver. Two detection ranges are analyzed, a so-called "defender" detection range and an "intruder" detection range. Both are conservative measures associated with CPoD equaling 0.5 during the transit of the submerged vessel. Predictions of the detection range are compared across independent attempts to solve the same problem with different modelling approaches. The spread of results (i.e., the "reproducibility" of the predictions) is discussed and reasons for differences are highlighted. Environmental conditions that strongly affect detection performance are discussed, as is the use of CPoD as a single-valued metric to describe detection performance.

Novel Modeling for the Calculation of the Center of Lateral Resistance Position of Different Ships Making Use of a Full Mission Bridge Simulator and AI Tools

Novel Modeling for the Calculation of the Center of Lateral Resistance Position of Different Ships Making Use of a Full Mission Bridge Simulator and AI Tools

Dynamic chaos unveiled: enhancing ship’s attitude time series prediction through spatiotemporal embedding and improved transformer model

Abstract During ship operations at sea, the vessel's attitude undergoes continuous changes due to various factors such as wind, waves, and its own motion. These influences are challenging to mathematically describe, and the changes in attitude are also influenced by multiple interconnected factors. Consequently, accurately predicting the ship's attitude presents significant challenges. Previous studies have demonstrated that phenomena like wind speed and wave patterns exhibit chaotic characteristics when affecting attitude changes. However, research on predicting ship attitudes lacks an exploration of whether chaotic characteristics exist and how they can be described and applied. This paper initially identifies the chaotic characteristics of ship attitude data through phase space reconstruction analysis and provides mathematical representations for them. Based on these identified chaotic characteristics, a&amp;#xD;Transformer model incorporating feature embedding layers is employed for time series prediction. Finally, a comparison with traditional methods validates the superiority of our proposed approach.&amp;#xD;

Assessing the accuracy of ship position through real-time measurements

Assessing the accuracy of ship position through real-time measurements

Marine information-seeking behaviours and AI chatbot impact on information discovery

Purpose This research investigates students’ information-seeking behaviours at the Indian Maritime University (IMU) and assesses the impact of AI chatbots on their marine science knowledge and awareness. The study aims to provide insights into the role of AI-driven solutions in enhancing knowledge sharing and the challenges faced in using AI tools for marine information retrieval. Design/methodology/approach The study used a stratified random sampling method, encompassing 152 respondents from IMU’s B.Sc. in Nautical Science and B. Tech in Marine Engineering programs. Data collection involved a structured electronic survey questionnaire. The analysis encompassed descriptive statistics using SPSS. Findings Information needs were met through diverse channels, with 57.9% of respondents using AI-driven chatbots for marine information retrieval. AI significantly recommended research papers (61.8%). The chatbot positively impacted marine science awareness and knowledge, with a mean satisfaction rating of approximately 3.3. Challenges included insufficient access to AI tools, data privacy concerns and accuracy issues. Originality/value This study contributes original insights into the information-seeking behaviours of marine students at IMU and the impact of AI chatbots on their knowledge and awareness. It highlights the multifaceted nature of marine information retrieval, the effectiveness of AI-driven solutions in enhancing knowledge sharing and the challenges that need to be addressed for the broader adoption of AI tools in this context.

Multi-Objective Optimization for Thrust Allocation of Dynamic Positioning Ship

Thrust allocation (TA) plays a critical role in the dynamic positioning system (DPS). The task of TA is to allocate the rotational speed and angle of each thruster to generate the generalized control forces. Most studies take TA as a single-objective optimization problem; however, TA is a multi-objective optimization problem (MOP), which needs to satisfy multiple conflicting allocation objectives simultaneously. This study proposes an improved multi-objective particle swarm optimization (IMOPSO) method to deal with the non-convex MOP of TA. The objective functions of reducing the allocation error, and minimizing the power consumption and the tear-and-wear of thrusters under physical constraints, are established and solved via MOPSO. To enhance the global seeking ability, the improved mutation strategy combined with the roulette wheel mechanism is adopted. It is shown through test data that IMOPSO converges better than multi-objective algorithms such as MOPSO and nondominated sorting genetic algorithm II (NSGA-II). Simulations are conducted for a DP ship with two propeller–rudder combinations. The simulation results with the single-objective PSO algorithm show that the proposed IMOPSO algorithm reduces thrust allocation errors in the three directions of surge, sway, and yaw by 48.48%, 39.64%, and 15.02%, respectively, and reduces power consumption by 44.53%, which demonstrates the feasibility and effectiveness of the proposed method.

Robust Fixed-Time Adaptive Fault-Tolerant Control for Dynamic Positioning of Ships with Thruster Faults

The ship dynamic positioning system has long been a subject of great interest due to the intricate and unpredictable nature of the maritime environment, which affects its dependability and timeliness. This study focuses on the issue of developing a robust, efficient, and adaptable fault-tolerant control system for ship dynamic positioning systems that experience thruster malfunctions. Firstly, we build the motion model of the ship’s dynamic positioning system with three degrees of freedom, as well as the model for faults in the thruster. A second-order fast fixed-time nonsingular sliding mode surface is formulated, and a robust adaptive control technique is introduced to counteract external environmental disturbances and model errors. The objective is to ensure rapid convergence of the system within a predetermined time frame. Simultaneously, combined with the fault-tolerant control technique, it is ensured that the dynamic positioning ship can still achieve system stability when thruster faults occur. In addition, the analysis of the Lyapunov stability criterion proves that the proposed fixed-time adaptive fault-tolerant control scheme can make the system tracking error converge within a fixed time. Finally, the effectiveness of the proposed control scheme is verified by numerical simulation results.

China’s Economic, Military, Science and Technological Emergence in International Politics: Implications for United States’ Hegemony

This study examined China’s emergence in international politics using the economic, military, science and technological pointers and its implications for United States’ hegemony. This topic was of interest because the struggle by states to assume the position of global political headman ship has been a constant decimal in international relations history. The contemporary international system elevates the United States as the triumphant superpower. The continued growth of China’s economy and the current modernization and buildup of its military has become a source of open concern for some scholars and statesmen both in the west and in the regions adjacent to China. The increasing influence of China in international affairs and her gradual move towards great power status have caused anxiety to the extent that how to deal with China is the puzzle of this new millennium. The questions that were of interest included; To what extent does China’s economic expansion, military modernization programme and advancement in science and technology threaten US hegemony in the International system? Neorealism theory was adopted for this study because its basic concepts of anarchy, structure, capability, distribution of power, polarity and national interest boosted the analytical strength of this study and enhanced understanding of the subject matter. In seeking answers to the questions raised, the study adopted the documentary research method and trend research design. Data was sourced from mainly secondary sources and analysed through a survey of the documents collected. Findings revealed that beside the aspect of China’s military modernization, its economic expansion and advancement in science and technology poses a real threat to US hegemony in those areas. It was recommended that both countries should increase investment in the other and also that a dialogue-based approach should be adopted to help each country consider how best to maximize cooperation whilst minimizing tension and conflict.

A novel regional ship collision risk assessment framework for multi-ship encounters in complex waters

To address the issue of precisely quantifying ship collision risk and identifying collision hotspots in complex waters, this study proposed a regional ship collision risk assessment framework that includes a multi-ship encounter recognition model, a multi-ship comprehensive collision risk assessment model, and a collision hotspot recognition model. Firstly, the directed distance density-based spatial clustering of applications with noise (DBSCAN) algorithm was proposed. Based on this algorithm, a multi-ship encounter recognition model was established to cluster ship positions and obtain ship encounter clusters. Subsequently, the multi-ship comprehensive collision risk assessment model was constructed for multi-ship encounter situations based on the hierarchical classification method, enabling the determination of each ship's Comprehensive Collision Risk Value (CCRV). Finally, the collision hotspot recognition model was built using the grid analysis method, which can identify areas with a higher risk of ship collision. The automatic identification system (AIS) data of the Yangtze River estuary were used to validate the effectiveness of our framework. The results show that our framework can accurately measure ship collisions risks and identify areas with high collision risks, offering valuable insights to maritime authorities, providing actionable insights for real-time ship collision risk monitoring.

Data-driven model for anti-pitching control of wave-piercing trimaran with stern-flap interceptor in waves

The control of pitching in wave-piercing trimarans helps improve crew comfort and navigation stability, providing a strong guarantee of safe and efficient ship operation. Current research on anti-pitching has mostly focused on control algorithms that use empirical formulas to calculate the stabilising moments directly. Little research has been conducted on appendage modelling. The Reynolds-averaged Navier–Stokes (RANS) method was employed to conduct a series of numerical simulations of waves on a trimaran equipped with a stern-flap interceptor with variable angles of attack. An optimal feature combination was designed by considering the spatial and temporal characteristics, such as the interaction between the stern-flap interceptor and hull, and the memory effect of the flow field. Based on long short-term memory (LSTM), a data-driven model of the stern-flap interceptor oriented towards anti-pitching control was constructed. In addition, the anti-pitching and drag-reduction mechanisms of the stern-flap interceptor were explored. The proposed model, which is oriented towards anti-pitching, establishes the relationship between the angle of attack of the appendage, the ship's attitude, and the stabilising moment applied to the hull. Experiments verified the accuracy and generalisation of the model. This study provides a theoretical basis for designing and developing an anti-pitching control system for wave-piercing trimarans.

A quasi-static mooring analysis approach for berthed ships

The existing literature extensively explores the environmental loads experienced by moored ships, a process known as mooring analysis. In order to model this analysis realistically, it is necessary to consider a number of variables, including ships' equations of motion, response amplitude operators, and mooring equipment capabilities. However, port authorities may lack comprehensive ship data. This study introduces a quasi-static equilibrium-state search method for berthed ships. It needs just basic ship particulars data and mooring arrangement data of berth and ship. The method enables the determination of crucial information such as mooring line load distribution, rope tension, rope failure and equilibrium ship position. Its versatility across ships and ports makes it noteworthy. Various analyses conducted on the method produce results with mean absolute percentage error values ranging from 0.57% to 2.23%, which are deemed significant and meaningful. Furthermore, the mathematical model of the method, which is currently considered to have three degrees of freedom, is open to improvement. The method has the potential to contribute significantly to various aspects, including the tail effect, the pretension effect, and the analysis of ropes with different stiffness values and capabilities.

Influence of welding parameters on the formation of U-rib fillet welds in single-sided welding of steel bridge panels

It is difficult to reach the requirement of 80% U-rib weld penetration in the practical application of single-sided welding of steel bridge panels. Meanwhile, full penetration has to be avoided. In this study, efforts are made in order to achieve fillet welds with 80% and above penetration consistently. The effect of welding parameters on the formation of single-sided U-rib fillet welds is investigated. This work has revealed that U-rib fillet weld penetration is presenting an upward trend as the welding current increases under specific welding conditions, and full penetration was observed at the current of 325 A. With the increasing distance between the filler wire and the root of the weld, the U-rib penetration reduces. As the torch angle increases during ship position welding, the U-rib penetration will first increase and then decrease. The weld formation of flat position welding is more stable and the U-rib weld penetration has been significantly improved. The optimum U-rib weld with penetration of 84.8% is achieved under the conditions of flat position welding with 285 A welding current, 44∘ torch angle, and 2[Formula: see text]mm distance between the wire and the root.

An approach to detect identity spoofing in AIS messages

Automatic identification system (AIS) is a maritime communication system that uses a transceiver to automatically exchange navigational data. These data help navigation and allow to monitor the maritime traffic. However, this system can be hacked and malicious users can easily transmit false data to mislead the coastguards or vessels navigating around. While previous research has proposed methods to detect these falsifications, none of them suggest strategies that detect AIS identity spoofing combining the tracking of the ship position and AIS transceiver’s carrier frequency offset (CFO). The CFO, caused by the carrier frequencies mismatch between emitter and receiver and Doppler effect, is used as a radiometric signature to identify materially every transceiver independently of its transmitted identity. It can drift over time and this is why it is tracked thanks to a Kalman filter (KF). In addition, position is also considered to reduce the miss probability of spoofing detection. The KF is noise adaptive to be robust against various CFO drifts and noise levels of the environment. The strategy is tested on real AIS data and the results demonstrate its efficacy: false alarm and miss probabilities were respectively 1% and 1.7%. These results show the ability of the test to correctly detect identity spoofing and the interest of CFO as a radiometric signature. This signature, used for the first time in an AIS application, could be used with other signatures in a future work to improve identity spoofing detection. This is why we made open source in GitHub our algorithm and the real AIS data used.

ETE-SRSP: An Enhanced Optimization of Tramp Ship Routing and Scheduling

In the contemporary tramp shipping industry, route optimization and scheduling are directly linked to enhancements in operations, economics, and the environment, making them key factors for the effective management of maritime transportation. To enhance effective ship-to-cargo matching and the refinement of maritime transportation itineraries, this paper introduces a time efficiency and carbon dioxide emission multi-objective optimization algorithm named ETE-SRSP (efficiency–time–emission multi-optimization algorithm). ETE-SRSP incorporates several factors, including the initial positions of ships, time windows for loading and unloading operations, and varying sailing speeds. Within the ETE-SRSP framework, pioneering an approach that integrates ballast and laden sailing velocities as decisional parameters, it employs a multi-objective optimization technique to investigate the intricate interplay between temporal efficiency and carbon dioxide emissions. Additionally, the model’s proficiency in mitigating emissions and managing costs is clearly demonstrated through the optimization of these objectives, thereby offering a robust framework for decision support. The experimental results show that the optimal sailing speeds derived from the ETE-SRSP, under typical time-weight scenarios, can achieve an optimal balance between emission reduction and cost control. In summary, this study underscores the optimization strategy’s potential to effectively address the maritime sector’s need for economic growth and ecological conservation, showcasing its practical value in the industry.

Penerapan Matriks Boston Consulting Group untuk Penanganan Muatan Barang Berbahaya pada Kapal Barang Nasional

The main problem of the research lies in the lack of training, competencies and skills of the crew due to the lack of discipline and the understanding of marine matters, especially related to dangerous goods handling on board. The purpose of the study is to analyze the position and management strategies offered in handling dangerous cargo, especially explosives on board of Sinar Palaran ship. The method to analyze the data was using Boston Consulting Group (BCG) Matrix analysis tool. The result shows that the intensity of dangerous goods cargo mishandling increase. Based on the analysis of Boston Consulting Group Matrix, the position of Sinar Palaran Ship is in Quadrant I, which indicates the company is facing the problem of low competence of the ship’s crew in handling dangerous goods cargo. The strategy offered through BCG Matrix is the strategy to develop, build and increase the intensity of training, discipline and maritime education for crew members to improve their competencies and skills in handling dangerous goods cargo.