Detecting invasive species with a bio-inspired semi-supervised neurocomputing approach: the case of Lagocephalus sceleratus

The need to protect the environment and biodiversity and to safeguard public health require the development of timely and reliable methods for the identification of particularly dangerous invasive species, before they become regulators of ecosystems. These species appear to be morphologically similar, despite their strong biological differences, something that complicates their identification process. Additionally, the localization of the broader space of dispersion and the development of invasive species are considered to be of critical importance in the effort to take proper management measures. The aim of this research is to create an advanced computational intelligence system for the automatic recognition, of invasive or another unknown species. The identification is performed based on the analysis of environmental DNA by employing machine learning methods. More specifically, this research effort proposes a hybrid bio-inspired computational intelligence detection approach. It employs extreme learning machines combined with an evolving Izhikevich spiking neuron model for the automated identification of the invasive fish species “Lagocephalus sceleratus” extremely dangerous for human health.

     

APIS: a software for model identification, simulation and dosage regimen calculations in clinical and experimental pharmacokinetics.

APIS is a software package based on mathematical modelling which provides a reliable approach in optimizing drug therapy. It was designed to assist clinicians in interpreting blood drug levels so that drug therapy may be better and more cost-effective. It is a methodological approach to describe, predict and control the kinetic behaviour of a drug. This software incorporates the principle of Bayesian procedures, i.e. one can use all available patient information (population) to determine patient-specific parameter estimates. These estimates can then be used to design an optimal and individualized drug regimen. APIS is an attractive and useful tool for clinical and experimental pharmacokinetics. APIS may be used on any IBM compatible computer using the Microsoft-Windows environment. The software is menu driven to provide a very user-friendly tool for analysing pharmacokinetic data and for designing dosage regimens.     

Revision of cemented fixation and cement-bone interface strength.

Interfacial shear strength between poly(methyl methacrylate) (PMMA) bone cement and cancellous bone was measured in bone samples from human proximal femora. Samples were prepared with fresh cement-bone, fresh cement inside a mantle of existing cement and with fresh cement-revised bone surfaces. Push-out tests to measure shear strength caused failure only at bone-cement interfaces; revised bone interfaces were 30 per cent weaker (P < 0.02) than primary interfaces. The clinical relevance is that revision of cemented joint arthroplasties may necessitate removal of components with sound cement-bone fixation. The practice of removing all traces of PMMA cement may not yield the optimal fixation; adhesion of fresh cement to freshly prepared surfaces of the existing cement might also be considered where circumstances are favourable.     

Head of the line arbitration of packet switches with combined input and output queueing

A single-stage non-blocking N × N packet switch is considered. Data units may be stored before switching at the inputs as well as after switching at the outputs. Some output buffering capacity is intended to achieve high throughput, whereas an additional input buffering capacity keeps losses due to input-buffer overflow reasonably low. The paper studies the impact on performance of the head of the line arbitration policy, i.e. the sequence which is used to transfer data units from the heads of input queues to each output queue. The investigation is based on two performance measures: the average delay and the maximum throughput of the switch. Closed-form expressions for the FCFS, LCFS and the ROS policies are obtained. The result of the average delay with the FCFS policy leads to a lower bound, and that with the LCFS policy to an upper bound for the average delay, corresponding to an arbitrary symmetric policy which does not use information related to the state of the input queues. It is shown that the maximum throughput does not depend on the head of the line arbitration policy. It depends only on the output-buffer size and the packet-size distribution. The cases of fixed and exponentially distributed packet sizes are studied. The effects of asymmetric policies which result in different behaviours of some of the input queues is also considered.     

Analysis of packet switches with input and output queuing

A single-stage nonblocking N*N packet switch with both output and input queuing is considered. The limited queuing at the output ports resolves output port contention partially. Overflow at the output queues is prevented by a backpressure mechanism and additional queuing at the input ports. The impact of the backpressure effect on the switch performance for arbitrary output buffer sizes and for N to infinity is studied. Two different switch models are considered: an asynchronous model with Poisson arrivals and a synchronous model with Bernoulli arrivals. The investigation is based on the average delay and the maximum throughput of the switch. Closed-form expressions for these performance measures are derived for operation with fixed size packets. The results demonstrate that a modest amount of output queuing, in conjunction with appropriate switch speedup, provides significant delay and throughput improvements over pure input queuing. The maximum throughput is the same for the synchronous and the asynchronous switch model, although the delay is different.<>     

Lattice mismatched InGaAs on silicon photodetectors grown by molecular beam epitaxy

In_0.5Ga_0.5As on silicon photodetectors, including three types of interdigitated-finger devices as well as linear photoconductors, were fabricated and measured. The InGaAs/Si structure was grown by molecular beam epitaxy and utilized a 100 Å GaAs intervening nucleation layer between the silicon substrate and the InGaAs layers, step-graded In_xGa_1?xAs layers, and an in-situ grown 40 Å thick GaAs surface layer, which substantially enhanced the metal-semiconductor barrier height (Φ_b = 0.67 V) for the InGaAs. Schottky diodes fabricated independently of the photodetectors had nearly ideal characteristics with an ideality factor (n) of 1.02 and a reverse breakdown voltage of 40 V. The interdigitated Schottky photodetectors showed dark currents between <3nA and 54 μA at a 3 V bias and initial photoresponse rise times in the range of 600 to 725 ps, comparable to similar InGaAs metal-semiconductor-metal photodetectors grown lattice matched on InP. The photoconductors fabricated in the same material had rise times in the range of 575 to 1300 ps, thus being slightly slower, and had dark currents of 7 to 80 mA. The responsivity of the photoconductors was typically greater than that of the diodes by a factor of five to fifteen. The results show potential for monolithic integration of InGaAs photodetectors on silicon substrates.     

Time-series modeling of fishery landings using ARIMA models and Fuzzy Expected Intervals software

Forecasting, using historic time-series data, has become an important tool for fisheries management. ARIMA modeling, Modeling for Optimal Forecasting techniques and Decision Support Systems based on fuzzy mathematics may be used to predict the general trend of a given fish landings time-series with increased reliability and accuracy. The present paper applies these three modeling methods to forecast anchovy fish catches landed in a given port (Thessaloniki, Greece) during 1979–2000 and hake and bonito total fish catches during 1982–2000. The paper attempts to assess the model's accuracy by comparing model results to the actual monthly fish catches of the year 2000. According to the measures of forecasting accuracy established, the best forecasting performance for anchovy was shown by the DSS model (MAPE = 28.06%, RMSE = 76.56, U-statistic = 0.67 and R² = 0.69). The optimal forecasting technique of genetic modeling improved significantly the forecasting values obtained by the selected ARIMA model. Similarly, the DSS model showed a noteworthy forecasting efficiency for the prediction of hake landings, during the year 2000 (MAPE = 2.88%, RMSE = 13.75, U-statistic = 0.19 and R² = 0.98), as compared to the other two modeling techniques. Optimal forecasting produced by combined modeling scored better than application of the simple ARIMA model. Overall, DSS results showed that the Fuzzy Expected Intervals methodology could be used as a very reliable tool for short-term predictions of fishery landings.