Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Filling-in Void and Sparse Regions in Protein Sequence Space by Protein-Like Artificial Sequences Enables Remarkable Enhancement in Remote Homology Detection Capability

Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

Flow pattern in chandler loop - the artificial thrombus formation

In this paper a hydrodynamic approach is used to analyse carefully the flow field inChandler loop--the artificial thrombus formation. The results obtained show that near thelower meniscus where the thrombus is formed, there is a back flow accompanied with asecondary flow and its mainflow is toward the meniscus, thus providing a favourable condi-tion for corpuscle aggregation. Our finding is valuable for studying the mechanism ofthrombus formation in artificial organ and in vivo.

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Generating artificial homologous proteins according to the representative family character in molecular mechanics properties - an attempt in validating an underlying rule of protein evolution

The molecular mechanics property is the foundation of many characters of proteins. Based on intramolecular hydrophobic force network, the representative family character underlying a protein’s mechanics property is described by a simple two-letter scheme. The tendency of a sequence to become a member of a protein family is scored according to this mathematical representation. Remote homologs of the WW-domain family could be easily designed using such a mechanistic signature of protein homology. Experimental validation showed that nearly all artificial homologs have the representative folding and bioactivity of their assigned family. Since the molecular mechanics property is the only consideration in this study, the results indicate its possible role in the generation of new members of a protein family during evolution.

Aspects of the fishing industry and an overview of artificial reefs and fish aggregating devices for increasing fisheries output and viability in Nigeria

Aspects of the Nigerian fishing industry are outlined to explain the concept of fishing systems viability which is often influenced by a combination of factors including biological productivity, as well as technical, economic and social factors. The productivity of the aquatic environments can be increased by the construction and installation of artificial reefs and fish aggregating devices. These man-made structures provide shelters, food and breeding grounds for fin fish and shell fish. The habitat enhancement techniques are appropriate, efficient, cheap and simple strategic options for increase in fish production. Recommendations for effective utilization and long term management are outlined.

Aspects of the washout of salmonid eggs. 1. Observations on the physical characteristics of real and artificial eggs, their rate of fall in a water column and their pattern of settlement in an experimental channel

When salmonid redds are disrupted by spates, the displaced eggs will drift downstream. The mean distance of travel, the types of locations in which the eggs resettle and the depth of reburial of displaced eggs are not known. Investigation of these topics under field conditions presents considerable practical problems, though the use of artificial eggs might help to overcome some of them. Attempts to assess the similarities and/or differences in performance between real and artificial eggs are essential before artificial eggs can validly be used to simulate real eggs. The present report first compares the two types of egg in terms of their measurable physical characteristics (e.g. dimensions and density). The rate at which eggs fall in still water will relate to the rate at which they are likely to resettle in flowing water in the field. As the rate of fall will be influenced by a number of additional factors (e.g. shape and surface texture) which are not easily measured directly, the rates of fall of the two types of egg have been compared directly under controlled conditions. Finally, comparisons of the pattern of settlement of the two types of egg in flowing water in an experimental channel have been made. Although the work was primarily aimed at testing the value of artificial eggs as a simulation of real eggs, several side issues more directly concerned with the properties of real eggs and the likely distance of drift in natural streams have also been explored. This is the first of three reports made on this topic by the author in 1984.

Tracking Pacific bluefin tuna (Thunnus thynnus orientalis) in the northeastern Pacific with an automated algorithm that estimates latitude by matching sea-surface-temperature data from satellites with temperature data from tags on fish

Data recovered from 11 popup satellite archival tags and 3 surgically implanted archival tags were used to analyze the movement patterns of juvenile northern bluefin tuna (Thunnus thynnus orientalis) in the eastern Pacific. The light sensors on archival and pop-up satellite transmitting archival tags (PSATs) provide data on the time of sunrise and sunset, allowing the calculation of an approximate geographic position of the animal. Light-based estimates of longitude are relatively robust but latitude estimates are prone to large degrees of error, particularly near the times of the equinoxes and when the tag is at low latitudes. Estimating latitude remains a problem for researchers using light-based geolocation algorithms and it has been suggested that sea surface temperature data from satellites may be a useful tool for refining latitude estimates. Tag data from bluefin tuna were subjected to a newly developed algorithm, called “PSAT Tracker,” which automatically matches sea surface temperature data from the tags with sea surface temperatures recorded by satellites. The results of this algorithm compared favorably to the estimates of latitude calculated with the lightbased algorithms and allowed for estimation of fish positions during times of the year when the lightbased algorithms failed. Three near one-year tracks produced by PSAT tracker showed that the fish range from the California−Oregon border to southern Baja California, Mexico, and that the majority of time is spent off the coast of central Baja Mexico. A seasonal movement pattern was evident; the fish spend winter and spring off central Baja California, and summer through fall is spent moving northward to Oregon and returning to Baja California.

Artificial Habitats for Fisheries Enhancement in the Australian Region

This paper outlines developments over about 20 years in the construction of and ecological research on artificial reefs, fish aggregation devices (FAD's), and other artificial habitats designed to enhance fish populations and fisheries in the Australian region (including New Zealand and Papua New Guinea). Work was initially carried out on multicomponent reefs using a variety of waste materials, as well as some specially constructed concrete and steel structures. Later studies concentrated on single-component reefs, again mainly using waste materials. Although no definitive conclusions were reached on the relative effectiveness of the different materials used, waste motor vehicle tires and derelict ships were generally judged to be the best all-around materials for single-component reef construction in sheltered estuarine and offshore marine environments, respectively, in this region. FAD's comprising polyvinylchloride pipe sparbuoys (or in some areas polyurethane foam floats) attached to railroad car wheel anchors by polyethylene rope and chain, and supporting attractor drapes of synthetic mesh webbing, also provedtobegenerallysuccessfulin thisarea. Overall conclusions for the Australian region include the predominant use of waste materials in artificial reef construction, which has been primarily aimed at recreational fisheries enhancement; the successful use of FAD's for both recreational and commercial fisheries enhancement; the need for further and better planned research into and monitoring of the effectiveness of both of these enhancement methods; and the need for future research into the effectiveness of unfished "artificial habitat reserves" in enhancing fisheries production from surrounding fished areas.