Due to the important role of hydrodynamic coefficients in the control and guidance of an autonomous underwater vehicle (AUV), sensitivity analysis is proposed here, as a preliminary step to motion control design. Taking the standard maneuvers, including turning circle and horizontal and vertical zigzag, the sensitivity of various hydrodynamic coefficients with respect to velocities and position is determined. Such analyses are then used to classify the model parameters into three categories, as non-sensitive coefficients, coefficients with low influence on the motion and more sensitive coefficients.
The paper examines three potential safety solutions for the protection of port workers, which are based on a junction of Radio Frequency IDentification (RFID), as an automatic identification, data collecting and positioning system from one side, and ZigBee, as a low energy consumption communication technology from another. The considered solutions are placed in the context of the individual needs and capacities of the developing Port of Bar in Montenegro (South East Europe), which has been operating in the transitional environment for the past two decades. The transitional circumstances prevent the port from adopting advanced occupational and environmental safety systems. Therefore we are proposing models for improving the workers' safety that are at the same time cost-effective, reliable and flexible. More precisely, the on port workers' body area sub networks formed by RFID active/passive devices are treated in the paper as end nodes of the ZigBee network. On the other hand, the forklifts' RFID warning systems are treated as the moving routers of the ZigBee network. Some simulation experiments with such RFID/ZigBee hybrid system in an OPNET environment have been implemented over the Port of Bar container and general cargo terminal layout, while corresponding conclusions have been derived, along with some directions for further research work in the field.
Since the U.S. National Science and Technology Council began implementing its plans for the development of intelligent structures in 2004, the Taiwan Communications Industry Alliance has been committed to applying communication and monitoring technologies in the construction industry to develop a market for intelligent houses. Accordingly, in this paper, relevant studies from January 2000 to December 2016 were collected from the Web of Science database. A key-route main path analysis of the text and data as well as a growth analysis of the research clusters in this field were performed to determine the main research topics and development trajectories. The development track for intelligent houses involves seven topics, namely general care, application of recognition sensors, energy management, medicine, application of the Internet of things, activity recognition systems, and monitoring technology. This paper offers a valuable literature review and analysis of this field and may acquaint scholars with related industrial development trends and academic progress.
Although the exact solutions for the free vibration problems regarding most of the non-uniform beams are not yet obtainable, this is not true for the special case when the equation of motion of a non-uniform beam can be transformed into that of an equivalent uniform beam. The nonlinearly tapered beam studied in this paper is a single-tapered beam with constant depth h_0 and varying width b(x) along its length in the form b(x) = b_0[1+α (x/L)]^4 , where b_0 is the minimum width, α is the taper constant, x is the axial coordinate and L is the total beam length. For the case of no concentrated elements (CEs) attaching to it, the exact solution for its lowest several natural frequencies and the associated mode shapes has been appeared in the existing literature, however, the exact solution for the free vibrations of the last tapered beam carrying various CEs in various boundary conditions (BCs) is not found yet due to complexity of the problem. This is the reason why this paper aims at studying the title problem by using the continuous-mass transfer matrix method (CTMM). It is different from the general uniform (or multi-step) beam carrying various CEs in that the nonlinearly tapered beam itself as well as the attached translational and rotational CEs must all be transformed into the equivalent ones in the derivations. In addition to the solution accuracy, one of the salient merits of the proposed method is that the order of the characteristic-equation matrix keeps constant (4 × 4) and does not increase with the total number of the CEs or the beam segments such as in the conventional finite element method (FEM), so that it needs less than 0.2% of the CPU time required by the FEM to achieve the exact solutions. The CEs on the nonlinearly tapered beam include lumped masses (with eccentricities and rotary inertias), translational springs and rotational springs. The formulation of this paper is available for various classical or non-classical BCs. In addition to comparing with the existing available data, most of the numerical results obtained from the proposed method are also compared with those of the FEM and good agreement is achieved.
This study developed and evaluated an integrated inventory model incorporating production programs and maintenance to model an imperfect process of a deteriorating production system in firm's activities of inbound logistics and production. Two preventive maintenance activities are performed during each production run period: perfect preventive maintenance and imperfect preventive maintenance. The perfect preventive maintenance's probability depends on the number of imperfect maintenance operations performed resulting from the last renewal cycle. The occurrence of a failure causes defective products which have a certain number of the ability of rework and not to be rework, and those cannot rework will lead to shortages. Experiments showed that the model optimizes the number of shipments and costs. The model is applied in various special cases to evaluate failure rate, including Weibull, geometric and learning effect. Finally a numerical example is presented.
Control units of electro-hydraulic double-axial folding machine can be classified as throttling type (valve-controlled) and volumetric type (pump-controlled). This paper focuses to compare their control performances. Valve-controlled folding machine (VCFM) has higher supply pressure, different circuit resistance between subsystems. Pump-controlled folding machine (PCFM) has variable working pressure and circuit resistance is slightly different. The folding machine is a coupled system and has significant structural interaction. This paper proposes coupled adaptive self-organizing sliding-mode fuzzy controllers to improve folding machine's level control performance. It found higher supply pressure of VCFM cause faster transient response, larger maximum overshoot via a variety of coupled intensity synchronous level control experiments. Experimental results indicate that their transient and steady state responses are similar, but pump-controlled folding machine has better level control accuracy than valve-controlled folding machine.
This paper presents an approach for solving a highly challenging problem in the preprocessing of hand-based biometrics, namely restoring IR palm-dorsum images captured in contactless scenarios and aligning regions of interest (ROIs) in the same regions on the various restored infrared (IR) palm-dorsum images captured from the same palm-dorsum. IR palm-dorsum images captured in contactless scenarios substantially increase the user-friendliness, security and sanitation of hand-based biometrics. However, images captured in contactless scenarios typically exhibit rotation, translation, scale and shear geometric transformations. These geometric transformations significantly reduce the accuracy of hand-based biometrics. An approach used to restore and align ROI on an IR palm-dorsum image is proposed to solve this problem. The proposed approach is based on a two-dimensional affine image transformation scheme used to restore the geometric transformations of the images, and an ROI alignment method based on finger-web positions. Thus, the proposed approach improves the user-friendliness, security, sanitation and accuracy of hand-based biometrics based on features extracted from the ROI. The principal characteristics of the proposed approach are no prior information on IR images being necessary, and no parameters being required to be preset. The experimental results indicated the effectiveness and feasibility of the proposed approach. The proposed approach improves accuracy, user-friendliness, security and sanitation and extends the application of hand-based biometrics for use in security access control systems.
The automatic recognition of traffic flow regions can provide decision support for ships' automatic route design and route planning. This study analyzes the characteristics of ships' trajectory structures and builds a course and distance model. Pearson correlation coefficients are used for measuring the similarities of the models and clustering trajectories, and kernel density estimation is used for estimating the probability density of clustered trajectories. An automatic recognition algorithm for traffic flow regions is proposed. This study examines ships' automatic identification system data in Laotieshan channel, China. The traffic separation scheme regions and traffic intersectional regions are recognized automatically, and the obtained results show good agreement with actual circumstances, thus verifying the applicability of the algorithm.
Upwelling is an essential mesoscale phenomenon as it contributes to regional as well as global marine biological productivity. The present study deals with utilization of QuikSCAT derived wind speed and wind direction for delineating the potential zones of coastal upwelling with its spatio-temporal variability and its corresponding influence on fishery resources. The Ekman mass transport and Ekman depth were used as the signatures to locate and extract the mesoscale properties of upwelling such as spatial extent and temporal persistence. The upwelling process is known to modulate the physical and biological properties of the ocean surface. In order to confirm the existence of upwelling, the extracted upwelling filaments were related with the satellite derived chlorophyll concentration (CC) and sea surface temperature (SST), the process so called synergistic analysis. It was observed from the synergistic analysis that the upwelling is associated with reduced SST and elevated CC which is an indication of suitable environment for fishes. The two to three fold increase was confirmed within the upwelling zone as compared to outside region. The presence of demersal species in the 30-50 m depth zone gives evidence for the aggregation of fishes in the upwelling zone. The combined analysis of upwelling, CC, SST and fishery catch data sets manifests that the upwelling support the large quantity of fishes as compared to other regions and the satellite based delineation and extraction of upwelling properties is useful for exploration of fishery resources.
Ocean color optic remote sensing has been used to estimate various biogeochemical constituents to monitor ocean environmental changes in coastal regions and global open oceans. However, the most problematic issue in utilizing ocean color measurements is cloud coverage. Thus, this study introduces a neural network (NN) algorithm to derive Chlorophyll a (Chl) concentrations, which are unavailable due to the presence of clouds. Because ocean color remote sensing depends on cloud coverage, microwave measurements, including sea-surface temperature, cloud, water vapor, precipitation, and winds, were used as inputs for the NN algorithm. Accordingly, the NN algorithm was designed to predict Chl using five inputs of microwave measurements and geolocation data. The correlation coefficient and root mean square error between the predicted and remotely sensed Chl concentrations were about 0.89 and 0.30 mg/m^3, respectively. Therefore, the developed NN algorithm enabled us to obtain Chl concentration during cloudy days, and even typhoon passages, as demonstrated in this study. However, Chl concentrations along coastal regions could not be predicted based on the inputs of the NN algorithm. Microwave remote sensing could not measure inhomogeneous emissivity for areas that were partially ocean and land, such as near-coastal regions.