Factors influencing choice of fishing location in Nankumba Peninsula: A case of study of gillnet and chilimira fisheries

This study was carried out to identify factors that influence choice of fishing location and carry out profitability analysis of Chilimira and Gillnet in different fishing locations. A survey using semi-structured questionnaire was administered to 99 Gillnet and 101 Chilimira fishers in Nankumba Peninsula in Mangochi District. The logit model was used to determine the factors influencing choice of fishing location among the fishers. The study showed that 92.1% of Chilimira fishers are operating in offshore areas while 69.7% Gillnet fishers are operating in inshore areas. Chilimira offshore fishers have higher daily average gross margins than their inshore counterparts and Gillnet fishers. However, they incurred more operating costs than the inshore Chilimira and Gillnet fishers. Furthermore, they find their fishing occupation more rewarding as evidenced by the higher returns to labour. The factors that influenced fisher’s choice of fishing location were Age of the fisher, type of fishing vessel and gear, possession of motor sail engine and access to information about previous day’s catch rates. Finally the study concluded that artisanal fishers in Malawi use different criteria in deciding where to fish. The criterion involves a complex interaction of biological, technological, personal and economical factors and time. However, the resource constrained artisanal fisher will need support to enable him exploit offshore fishery resources. Consequently the study recommends that appropriate fishery development interventions by the government and other stakeholders must adapt to the economics and lifestyles driving the artisanal fishers to fish in particular locations and therefore, build on this foundation to improve the existing fishing technologies.

An environmentally based growth model that uses finite difference calculus with maximum likelihood method: its application to the brackish water bivalve Corbicula japonica in Lake Abashiri, Japan

We present a growth analysis model that combines large amounts of environmental data with limited amounts of biological data and apply it to Corbicula japonica. The model uses the maximum-likelihood method with the Akaike information criterion, which provides an objective criterion for model selection. An adequate distribution for describing a single cohort is selected from available probability density functions, which are expressed by location and scale parameters. Daily relative increase rates of the location parameter are expressed by a multivariate logistic function with environmental factors for each day and categorical variables indicating animal ages as independent variables. Daily relative increase rates of the scale parameter are expressed by an equation describing the relationship with the daily relative increase rate of the location parameter. Corbicula japonica grows to a modal shell length of 0.7 mm during the first year in Lake Abashiri. Compared with the attain-able maximum size of about 30 mm, the growth of juveniles is extremely slow because their growth is less susceptible to environmental factors until the second winter. The extremely slow growth in Lake Abashiri could be a geographical genetic variation within C. japonica.

El Niño reconstructions and confirmation of a pan-Californian model via Radiolarian evidence

Radiolarian number and/or flux rates extracted from Holocene and fossil sediments are used to help detect the presence of, type of (weak or strong), and exact location of the depocenter under an El Niño. These data, along with known provenances of certain radiolarians, support an earlier model that suggests a weak El Niño is a northern and coupled expression of a more southerly strong component dominated by eastern tropical Pacific water underlain by California current and gyre water.

Modified Kanerva model. Results for real time word recognition

This paper describes results obtained using the modified Kanerva model to perform word recognition in continuous speech after being trained on the multi-speaker Alvey 'Hotel' speech corpus. Theoretical discoveries have recently enabled us to increase the speed of execution of part of the model by two orders of magnitude over that previously reported by Prager & Fallside. The memory required for the operation of the model has been similarly reduced. The recognition accuracy reaches 95% without syntactic constraints when tested on different data from seven trained speakers. Real time simulation of a model with 9,734 active units is now possible in both training and recognition modes using the Alvey PARSIFAL transputer array. The modified Kanerva model is a static network consisting of a fixed nonlinear mapping (location matching) followed by a single layer of conventional adaptive links. A section of preprocessed speech is transformed by the non-linear mapping to a high dimensional representation. From this intermediate representation a simple linear mapping is able to perform complex pattern discrimination to form the output, indicating the nature of the speech features present in the input window.

An experimental model of relay deployment planning tool for a wireless sensor network system to monitor civil engineering structures

It is essential to monitor deteriorated civil engineering structures cautiously to detect symptoms of their serious disruptions. A wireless sensor network can be an effective system for monitoring civil engineering structures. It is fast to deploy sensors especially in difficult-to-access areas, and it is extendable without any cable extensions. Since our target is to monitor deteriorations of civil engineering structures such as cracks at tunnel linings, most of the locations of sensors are known, and sensors are not required to move dynamically. Therefore, we focus on developing a deployment plan of a static network in order to reduce the value of a cost function such as initial installation cost and summation of communication distances of the network. The key issue of the deployment is the location of relays that forward sensing data from sensors to a data collection device called a gateway. In this paper, we propose a relay deployment-planning tool that can be used to design a wireless sensor network for monitoring civil engineering structures. For the planning tool, we formalize the model and implement a local search based algorithm to find a quasi-optimal solution. Our solution guarantees two routings from a sensor to a gateway, which can provide higher reliability of the network. We also show the application of our experimental tool to the actual environment in the London Underground.

Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.

Multi-Modal Image Retrieval from Construction Databases and Model-Based Systems

In the modern and dynamic construction environment it is important to access information in a fast and efficient manner in order to improve the decision making processes for construction managers. This capability is, in most cases, straightforward with today’s technologies for data types with an inherent structure that resides primarily on established database structures like estimating and scheduling software. However, previous research has demonstrated that a significant percentage of construction data is stored in semi-structured or unstructured data formats (text, images, etc.) and that manually locating and identifying such data is a very hard and time-consuming task. This paper focuses on construction site image data and presents a novel image retrieval model that interfaces with established construction data management structures. This model is designed to retrieve images from related objects in project models or construction databases using location, date, and material information (extracted from the image content with pattern recognition techniques).

Seafloor-riser interaction model

Fatigue stresses associated with extreme storms, vessel movements, and vortex-induced vibrations are critical to the performance of steel catenary risers. The critical location for fatigue damage often occurs within the touchdown zone, where cyclic interaction of the riser with the seabed occurs. Developing a model for seabed stiffness requires characterization of a number of complex nonlinear processes including trench formation, nonlinear soil stiffness, soil suction, and breakaway of the riser from the seafloor. The analytical framework utilized in this research considers the riser-seafloor interaction problem in terms of a pipe resting on a bed of springs, the stiffness characteristics of which are described by nonlinear load-deflection (P-y) curves. The P-y model allows for first penetration and uplift, as well as repenetration and small range motions within the bounding loop defined by extreme loading. The backbone curve is constructed from knowledge of the soil strength, the rate of strength increase with depth, trench width, and two additional parameters, while three parameters are necessary for the cyclic response. © ASCE 2009.

Delayed control of a Moore-Greitzer axial compressor model

Several feedback control laws have appeared in the literature concerning the stabilization of the nonlinear Moore-Greitzer axial compression model. Motivated by magnitude and rate limitations imposed by the physical implementation of the control law, Larsen et al. studied a dynamic implementation of the S-controller suggested by Sepulchre and Kokotović. They showed the potential benefit of implementing the S-controller through a first-order lag: while the location of the closed-loop equilibrium achieved with the static control law was sensitive to poorly known parameters, the dynamic implementation resulted in a small limit cycle at a very desirable location, insensitive to parameter variations. In this paper, we investigate the more general case when the control is applied with a time delay. This can be seen as an extension of the model with a first-order lag. The delay can either be a result of system constraints or be deliberately implemented to achieve better system behavior. The resulting closed-loop system is a set of parameter-dependent delay differential equations. Numerical bifurcation analysis is used to study this model and investigate whether the positive results obtained for the first-order model persist, even for larger values of the delay.

Experimental study of the effects of temperature variation on droplet size and wetness fraction in a low-pressure model steam turbine

The three-stage low-pressure model steam turbine at the Institute of Thermal Turbomachinery and Machinery Laboratory (ITSM) was used to study the impact of three different steam inlet temperatures on the homogeneous condensation process and the resulting wetness topology. The droplet spectrum as well as the particle number concentration were measured in front of the last stage using an optical-pneumatic probe. At design load, condensation starts inside the stator of the second stage. A change in the steam inlet temperature is able to shift the location of condensation onset within the blade row up- or downstream and even into adjoining blade passages, which leads to significantly different local droplet sizes and wetness fractions due to different local expansion rates. The measured results are compared to steady three-dimensional computational fluid dynamics calculations. The predicted nucleation zones could be largely confirmed by the measurements. Although the trend of measured and calculated droplet size across the span is satisfactory, there are considerable differences between the measured and computed droplet spectrum and wetness fractions. © IMechE 2013 Reprints and permissions: sagepub.co.uk/ journalsPermissions.nav.

Two-component model for the interstellar scattering in direction to the Vela pulsar

This paper discusses a rigorous treatment of the refractive scintillation of pulsar PSR B0833-45 caused by a two-component interstellar scattering medium. It is assumed that the interstellar scattering medium is composed of a thin screen ISM and an extended interstellar medium. We consider that the scattering of the thin screen concentrates in a thin layer presented by a delta function distribution and that the scattering density of the extended irregular medium satisfies the Gaussian distribution. We investigate and develop equations for the flux density structure function corresponding to this two-component ISM geometry in the scattering density distribution and compare our result with that of the Vela pulsar observations. We conclude that the refractive scintillation caused by this two-component ISM scattering gives a more satisfactory explanation for the observed flux density variation of the Vela pulsar than does the single extended medium model. The level of refractive scintillation is strongly sensitive to the distribution of scattering material along the line of sight. The logarithmic slope of the structure function is sensitive to thin screen location and is relatively insensitive to the scattering strength of the thin screen medium. Therefore, the proposed model can be applied to interpret the structure function of flux density observed in pulsar PSR B0833-45. The result suggests that the medium consists of a discontinuous distribution of plasma turbulence embedded in the Vela supernova remnant. Thus our work provides some insight into the distribution of the scattering along the line of sight to the Vela pulsar.

Performance of supersonic model combustors with staged injections of supercritical aviation kerosene

Supersonic model combustors using two-stage injections of supercritical kerosene were experimentally investigated in both Mach 2.5 and 3.0 model combustors with stagnation temperatures of approximately 1,750 K. Supercritical kerosene of approximately 760 K was prepared and injected in the overall equivalence ratio range of 0.5-1.46. Two pairs of integrated injector/flameholder cavity modules in tandem were used to facilitate fuel-air mixing and stable combustion. For single-stage fuel injection at an upstream location, it was found that the boundary layer separation could propagate into the isolator with increasing fuel equivalence ratio due to excessive local heat release, which in turns changed the entry airflow conditions. Moving the fuel injection to a further downstream location could alleviate the problem, while it would result in a decrease in combustion efficiency due to shorter fuel residence time. With two-stage fuel injections the overall combustor performance was shown to be improved and kerosene injections at fuel rich conditions could be reached without the upstream propagation of the boundary layer separation into the isolator. Furthermore, effects of the entry Mach number and pilot hydrogen on combustion performance were also studied.

An Efficient Correspondence Based Algorithm for 2D and 3D Model Based Recognition

A polynomial time algorithm (pruned correspondence search, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image, is presented. Efficient verification algorithms, based on a linear representation of location constraints, are given for the case of affine transformations among vector spaces and for the case of rigid 2D and 3D transformations with scale. Some preliminary experiments suggest that PCS is a practical algorithm. Its similarity to existing correspondence based algorithms means that a number of existing techniques for speedup can be incorporated into PCS to improve its performance.

The dayside high-latitude trough under quiet geomagnetic conditions: Radio tomography and the CTIP model

Pryse, Sian; Dewis, K.L.; Middleton, H.R.; Balthazor, R.L., (2005) 'The dayside high-latitude trough under quiet geomagnetic conditions: Radio tomography and the CTIP model', Annales Geophysicae 23(4) pp.1199-1206 RAE2008

On the Geographic Location of Internet Resources

One relatively unexplored question about the Internet's physical structure concerns the geographical location of its components: routers, links and autonomous systems (ASes). We study this question using two large inventories of Internet routers and links, collected by different methods and about two years apart. We first map each router to its geographical location using two different state-of-the-art tools. We then study the relationship between router location and population density; between geographic distance and link density; and between the size and geographic extent of ASes. Our findings are consistent across the two datasets and both mapping methods. First, as expected, router density per person varies widely over different economic regions; however, in economically homogeneous regions, router density shows a strong superlinear relationship to population density. Second, the probability that two routers are directly connected is strongly dependent on distance; our data is consistent with a model in which a majority (up to 75-95%) of link formation is based on geographical distance (as in the Waxman topology generation method). Finally, we find that ASes show high variability in geographic size, which is correlated with other measures of AS size (degree and number of interfaces). Among small to medium ASes, ASes show wide variability in their geographic dispersal; however, all ASes exceeding a certain threshold in size are maximally dispersed geographically. These findings have many implications for the next generation of topology generators, which we envisage as producing router-level graphs annotated with attributes such as link latencies, AS identifiers and geographical locations.