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Aiming to avoid personal injury caused by the failure of timely medical assistance following a fall by seafarer members working on ships, research on the detection of seafarer's falls and timely warnings to safety officers can reduce the loss and severe consequences of falls to seafarers. To improve the detection accuracy and real-time performance of the seafarer fall detection algorithm, a seafarer fall detection algorithm based on BlazePose-LSTM is proposed. This algorithm can automatically extract the human body key point information from the video image obtained by the vision sensor, analyze its internal data correlation characteristics, and realize the process from RGB camera image processing to seafarer fall detection. This fall detection algorithm extracts the human body key point information through the optimized BlazePose human body key point information extraction network. In this section, a new method for human bounding-box acquisition is proposed. In this study, a head detector based on the Vitruvian theory was used to replace the pre-trained SSD body detector in the BlazePose preheating module. Simultaneously, an offset vector is proposed to update the bounding box obtained. This method can reduce the frequency of repeated use of the head detection module. The algorithm then uses the long short-term memory neural network to detect seafarer falls. After extracting fall and related behavior data from the URFall public data set and FDD public data set to enrich the self-made data set, the experimental results show that the algorithm can achieve 100% accuracy and 98.5% specificity for the seafarer's falling behavior, indicating that the algorithm has reasonable practicability and strong generalization ability. The detection frame rate can reach 29 fps on a CPU, which can meet the effect of real-time detection. The proposed method can be deployed on common vision sensors.
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Algoritmos , Redes Neurais de Computação , Humanos , Processamento de Imagem Assistida por Computador , NaviosRESUMO
Maritime surveillance videos provide crucial on-spot kinematic traffic information (traffic volume, ship speeds, headings, etc.) for varied traffic participants (maritime regulation departments, ship crew, ship owners, etc.) which greatly benefits automated maritime situational awareness and maritime safety improvement. Conventional models heavily rely on visual ship features for the purpose of tracking ships from maritime image sequences which may contain arbitrary tracking oscillations. To address this issue, we propose an ensemble ship tracking framework with a multi-view learning algorithm and wavelet filter model. First, the proposed model samples ship candidates with a particle filter following the sequential importance sampling rule. Second, we propose a multi-view learning algorithm to obtain raw ship tracking results in two steps: extracting a group of distinct ship contour relevant features (i.e., Laplacian of Gaussian, local binary pattern, Gabor filter, histogram of oriented gradient, and canny descriptors) and learning high-level intrinsic ship features by jointly exploiting underlying relationships shared by each type of ship contour features. Third, with the help of the wavelet filter, we performed a data quality control procedure to identify abnormal oscillations in the ship positions which were further corrected to generate the final ship tracking results. We demonstrate the proposed ship tracker's performance on typical maritime traffic scenarios through four maritime surveillance videos.
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Contact geometry significantly influences adhesive force measurements and modeling for adhesion/friction studies where an AFM colloidal probe technique has been extensively employed. Here we present a systematic study on the topography alteration of silica microspheres sliding on mica, sapphire, and glass substrates under ambient conditions at a relative humidity of 30-55% and the consequential adhesion behaviors of worn microspheres through AFM direct force measurements and theoretical modeling. The wearing of microspheres creates a truncated platform, which is largest for sliding on glass substrates. On the platform are nanoasperities consisting of wear debris and airborne particulate contaminants. Variations in adhesive forces with sliding time and testing modes as well as the effect of surface roughness of substrates are explained within the theoretical framework of nanoasperity-mediated capillary and van der Waals forces. The drawbacks of the present reverse-imaging method for microsphere topography examination, and numerous sources of errors associated with the extraction of key parameters for force modeling, are discussed in detail. The results will also have important implications for more reliable AFM colloidal probe technique and its application in adhesion and tribological studies.
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Catalytic methods to couple alcohol and alkene feedstocks are highly valuable in synthetic chemistry. The direct oxidative coupling of primary alcohols and alkenes offers a streamlined approach to ketone synthesis. Currently, available methods are based on transition metal-catalyzed alkene hydroacylation, which involves the generation of an electrophilic aldehyde intermediate from primary alcohol dehydrogenation. These methods generally require high reaction temperatures and a high loading of precious metal catalysts and are predominantly effective for branch-selective reactions with electron-rich alkenes. Herein, we designed a dual photo/cobalt-catalytic method to manipulate the reactivity of nucleophilic ketyl radicals for the synthesis of ketones from primary alcohols and alkenes in complementary reactivity and selectivity. This protocol exhibits exceptional scope across both primary alcohols and alkenes with high chemo- and regio-selectivity under mild reaction conditions. Mechanism investigations reveal the essential role of cobalt catalysis in enabling efficient catalysis and broad substrate scope.
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Currently, osteoporosis-related fractures become the most cutting-edge problem of diabetes-related complications. Rational diet is not only the basis of glycemic management in type 2 diabetes patients, but also the direction of diabetic bone health. This review highlights the importance of micronutrient supplementation (including calcium, magnesium, zinc, vitamin D, vitamin K, and vitamin C) for patients with T2DM, as well as describing the constructive intermediary role of gut flora between T2DM and bone through nutrients predominantly high in dietary fiber. In addition, it is recommended to combine the Mediterranean dietary pattern with other diversified management approaches to prevent OP. Therefore, this provides a theoretical basis for the potential role of islet ß-cells in promoting bone health.
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Background: In recent years, with the rapidly development of economic globalization, residents' dietary structure has undergone major changes, and diet have emerged as an important environmental factors linked to the increased incidence of obesity. Therefore, evaluating the overall dietary quality and structure of residents, further clarifying the main dietary factors that lead to disease occurrence, is of great practical significance for disease prevention and control. Methods: Baseline data from the China Multi-Ethnic Cohort study (CMEC), Han people living in high-altitude and cold regions of Yunnan Province, which was 1518 participants. In this study, the dietary balance index (DBI-16) was used (i) To evaluate the dietary quality of Han nationality residents 30-79 years old in the Yunnan plateau; (ii) To analyze the correlation between the dietary quality and overweight/obesity; (iii) And to provide reference basis of nutritional intervention for local residents and explore the main dietary factors affecting their health status. Results: The dietary structure of the Han nationality residents in the cold regions of Yunnan plateau is unreasonable. Firstly, the intake of cereals, fruits, dairy, eggs and fishes is insufficient to varying degrees, while the intake of beans, poultry, and cooking oil is relatively high. Secondly, the dietary patterns of normal groups, the overweight and obese groups obeyed the A, E, H and I dietary patterns, and the serum Leptin and adipocyte fatty acid binding protein (A-FABP) levels of the overweight and obese group were higher than the normal group between the different dietary patterns (P < 0.05, r > 0). Additionally, excessive dietary intake was positively correlated with a higher serum UCP1 level (P < 0.05, r > 0). In comparison, insufficient dietary intake was positively correlated with a higher serum A-FABP level (P < 0.05, r > 0). Conclusion: Through the DBI-16, it is found that the dietary structure of the Han nationality residents in the cold regions of Yunnan plateau was in a serious imbalance state, and nutritional guidance and intervention should be further strengthened.
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The development of cost-effective and energy-efficient technologies for the stabilization of organic wastewater by microalgae has been essential and sought after. In the current study, GXU-A4 was isolated from an aerobic tank treating molasses vinasse (MV) and identified as Desmodesmus sp. based on its morphology, rbcL, and ITS sequences. It exhibited good growth with a high lipid content and chemical oxygen demand (COD) when grown using MV and the anaerobic digestate of MV (ADMV) as the growth medium. Three distinct COD concentrations for wastewater were established. Accordingly, GXU-A4 removed more than 90% of the COD from molasses vinasse (MV1, MV2, and MV3) with initial COD concentrations of 1193 mgL-1, 2100 mgL-1, and 3180 mgL-1, respectively. MV1 attained the highest COD and color removal rates of 92.48% and 64.63%, respectively, and accumulated 47.32% DW (dry weight) of lipids and 32.62% DW of carbohydrates, respectively. Moreover, GXU-A4 grew rapidly in anaerobic digestate of MV (ADMV1, ADMV2, and ADMV3) with initial COD concentrations of 1433 mgL-1, 2567 mgL-1, and 3293 mgL-1, respectively. Under ADMV3 conditions, the highest biomass reached 13.81 g L-1 and accumulated 27.43% DW of lipids and 38.70% DW of carbohydrates, respectively. Meanwhile, the removal rates of NH4-N and chroma in ADMV3 reached 91.10% and 47.89%, respectively, significantly reducing the concentration of ammonia nitrogen and color in ADMV. Thus, the results demonstrate that GXU-A4 has a high fouling tolerance, a rapid growth rate in MV and ADMV, the ability to achieve biomass accumulation and nutrient removal from wastewater, and a high potential for MV recycling.
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Microalgas , Águas Residuárias , Melaço , Carboidratos , Biomassa , Nitrogênio , LipídeosRESUMO
The purpose of the study is to solve problems, i.e., increasingly significant processing delay of massive monitoring data and imbalanced tasks in the scheduling and monitoring center for a railway network. To tackle these problems, a method by using a smooth weighted round-robin scheduling based on backpressure flow control (BF-SWRR) is proposed. The method is developed based on a model for message queues and real-time streaming computing. By using telemetry data flow as input data sources, the fields of data sources are segmented into different sets by using a distributed model of stream computing parallel processing. Moreover, the round-robin (RR) scheduling method for the distributed server is improved. The parallelism, memory occupancy, and system delay are tested by taking a high-speed train section of a certain line as an example. The result showed that the BF-SWRR method for clusters can control the delay to within 1 s. When the parallelism of distributed clusters is set to 8, occupancy rates of the CPU and memory can be decreased by about 15%. In this way, the overall load of the cluster during stream computing is more balanced.
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Armazenamento e Recuperação da Informação/métodos , Algoritmos , Análise por Conglomerados , Computadores , Fontes de Energia Elétrica/tendências , Armazenamento e Recuperação da Informação/tendências , Modelos Teóricos , SoftwareRESUMO
Early warning on the ship deficiency is crucial for enhancing maritime safety, improving maritime traffic efficiency, reducing ship fuel consumption, etc. Previous studies focused on the ship deficiency exploration by mining the relationships between the ship physical deficiencies and the port state control (PSC) inspection results with statistical models. Less attention was paid to discovering the correlation rules among various parent ship deficiencies and subcategories. To address the issue, we proposed an improved Apriori model to explore the intrinsic mutual correlations among the ship deficiencies from the PSC inspection dataset. Four typical ship property indicators (i.e., ship type, age, deadweight and gross tonnage) were introduced to analyze the correlations for the ship parent deficiency categories and subcategories. The findings of our research can provide basic guidelines for PSC inspections to improve the ship inspection efficiency and maritime safety.
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Mineração de Dados , Saneamento/estatística & dados numéricos , Navios , Algoritmos , Modelos Estatísticos , SegurançaRESUMO
In order to obtain the information of the vehicle tags in adverse traffic conditions, we proposed a novel reservation framework named reservation to cancel idle-dynamic frame slotted ALOHA (RTCI-DFSA) algorithm. Firstly, the framework employed reservation mechanism to remove idle slot, and thus improve the system identification efficiency. Secondly, the vehicle information was identified by the tag serialization polling identification method. The experimental results showed that the proposed RTCI-DFSA algorithm performed better than the traditional frame slotted ALOHA (FSA) and dynamic frame slotted ALOHA (DFSA) algorithms. More specifically, the tag loss rate of the proposed framework is significantly lower than the frame length fixed and conventional dynamic vehicle identification algorithms. In addition, the experimental results demonstrated that the throughput rate of the proposed algorithm increased from 0.368 to 0.6. Besides, the identification efficiency and applicability of the proposed framework were both higher than other tag identification algorithms.
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Acidentes de Trânsito/prevenção & controle , Inteligência Artificial , Dispositivo de Identificação por Radiofrequência , AlgoritmosRESUMO
Understanding correlation between influential factors and insurance losses is beneficial for insurers to accurately price and modify the bonus-malus system. Although there have been a certain number of achievements in insurance losses and claims modeling, limited efforts focus on exploring the relative role of accidents characteristics in insurance losses. The primary objective of this study is to evaluate the influential priority of transit accidents attributes, such as the time, location and type of accidents. Based on the dataset from Washington State Transit Insurance Pool (WSTIP) in USA, we implement several key algorithms to achieve the objectives. First, K-means algorithm contributes to cluster the insurance loss data into 6 intervals; second, Grey Relational Analysis (GCA) model is applied to calculate grey relational grades of the influential factors in each interval; in addition, we implement Naive Bayes model to compute the posterior probability of factors values falling in each interval. The results show that the time, location and type of accidents significantly influence the insurance loss in the first five intervals, but their grey relational grades show no significantly difference. In the last interval which represents the highest insurance loss, the grey relational grade of the time is significant higher than that of the location and type of accidents. For each value of the time and location, the insurance loss most likely falls in the first and second intervals which refers to the lower loss. However, for accidents between buses and non-motorized road users, the probability of insurance loss falling in the interval 6 tends to be highest.
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Acidentes de Trânsito , Seguro , Setor Público , Meios de Transporte , AlgoritmosRESUMO
Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model-Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired.
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Grade variation on interstate highways affects the roadway geometric design, vehicle performance and driver behavior, thus possibly exerting an unexpected effect on vehicular speed. Hence, determining the internal relationship between grade and speed is important and useful for drivers, traffic regulators and other traffic participants. However, the problem with performing this research is the lack of large-scale gradient and speed data. Google Earth (GE) provides an application programming interface for extracting elevation data worldwide. The elevation dataset from GE can be easily converted to grade data. In addition, our team has collected and stored speed series data for different freeways over several years. Based on the above obtainable grade and speed datasets, we conducted research on the effect of grades on free flow speeds from two perspectives. First, the influence of grades on speed was analyzed from both quantitative and qualitative aspects. The analysis of the distributions of four typical types of speeds demonstrated a decreasing tendency as the speed increased. Steeper grades generated a more intense speed fluctuation in terms of the four types of speeds. Second, a model based on the Student's t-test was developed to evaluate the level of significant difference among speed series under neighboring grades. The Student's t-test demonstrated that adjacent grades do not significantly influence the speeds. In summary, speeds under different grades showed obviously different tendencies. The findings of this study can help transport authorities set more reasonable speed limits and improve the geometric design of interstates with grade variation constraints.
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Acidentes de Trânsito , Condução de Veículo , Meios de Transporte , Sistemas de Informação Geográfica , Humanos , Modelos Teóricos , Washington , Tempo (Meteorologia)RESUMO
Drivers gather traffic information primarily by means of their vision. Especially during complicated maneuvers, such as overtaking, they need to perceive a variety of characteristics including the lateral and longitudinal distances with other vehicles, the speed of others vehicles, lane occupancy, and so on, to avoid crashes. The primary object of this study is to examine the appropriate visual search patterns during overtaking maneuvers on freeways. We designed a series of driving simulating experiments in which the type and speed of the leading vehicle were considered as two influential factors. One hundred and forty participants took part in the study. The participants overtook the leading vehicles just like they would usually do so, and their eye movements were collected by use of the Eye Tracker. The results show that participants' gaze durations and saccade durations followed normal distribution patterns and that saccade angles followed a log-normal distribution pattern. It was observed that the type of leading vehicle significantly impacted the drivers' gaze duration and gaze frequency. As the speed of a leading vehicle increased, subjects' saccade durations became longer and saccade angles became larger. In addition, the initial and destination lanes were found to be key areas with the highest visual allocating proportion, accounting for more than 65% of total visual allocation. Subjects tended to more frequently shift their viewpoints between the initial lane and destination lane in order to search for crucial traffic information. However, they seldom directly shifted their viewpoints between the two wing mirrors.