The detection and classification of blast cell in Leukaemia Acute Promyelocytic Leukaemia (AML M3) blood using simulated annealing and neural networks

This paper was delivered at AIME 2011: 13th Conference on Artifical Intelligence in Medicine.This paper presents a method for the detection and classification of blast cells in M3 with others sub-types using simulated annealing and neural networks. In this paper, we increased our test result from 10 images to 20 images. We performed Hill Climbing, Simulated Annealing and Genetic Algorithms for detecting the blast cells. As a result, simulated annealing is the “best” heuristic search for detecting the leukaemia cells. From the detection, we performed features extraction on the blast cells and we classifying based on M3 and other sub-types using neural networks. We received convincing result which has targeting around 97% in classifying of M3 with other sub-types. Our results are based on real world image data from a Haematology Department.Universiti Sains Islam Malaysia and the Ministry of Higher Education, Malaysi

Electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Universiti Tun Hussein Onn Malaysia (UTHM) is a developing Malaysian Technical University. There is a great development of UTHM since its formation in 1993. Therefore, it is crucial to have accurate future electricity consumption forecasting for its future energy management and saving. Even though there are previous works of electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS), but most of their data are multivariate data. In this study, we have only univariate data of UTHM electricity consumption from January 2009 to December 2018 and wish to forecast 2019 consumption. The univariate data was converted to multivariate and ANFIS was chosen as it carries both advantages of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS). ANFIS yields the MAPE between actual and predicted electricity consumption of 0.4002% which is relatively low if compared to previous works of UTHM electricity forecasting using time series model (11.14%), and first-order fuzzy time series (5.74%), and multiple linear regression (10.62%)

A node-wise analysis of the uterine muscle networks for pregnancy monitoring

The recent past years have seen a noticeable increase of interest in the correlation analysis of electrohysterographic (EHG) signals in the perspective of improving the pregnancy monitoring. Here we propose a new approach based on the functional connectivity between multichannel (4x4 matrix) EHG signals recorded from the women abdomen. The proposed pipeline includes i) the computation of the statistical couplings between the multichannel EHG signals, ii) the characterization of the connectivity matrices, computed by using the imaginary part of the coherence, based on the graph-theory analysis and iii) the use of these measures for pregnancy monitoring. The method was evaluated on a dataset of EHGs, in order to track the correlation between EHGs collected by each electrode of the matrix (called node-wise analysis) and follow their evolution along weeks before labor. Results showed that the strength of each node significantly increases from pregnancy to labor. Electrodes located on the median vertical axis of the uterus seemed to be the more discriminant. We speculate that the network-based analysis can be a very promising tool to improve pregnancy monitoring.Comment: 4 pages, 3 figures, accepted in the IEEE EMBC conferanc

Design zero-voltage switching DC-DC buck converter

This report proposes an integrated, high switching frequency, zero-voltage-switching dc-dc buck converter for battery charger application. The design and analysis of dc�dc buck converter with integrated inductor is presented. The converter has been optimized to convert 12V input voltage to 5V at 1.5A maximum load current at 50MHz switching frequency. The converter has been simulated using an ORCAD 16.5 based simulation tool and result show that the switching losses using zero�voltage-switching technique is less compared to conventional buck converter

Efficient Dynamic Compressor Optimization in Natural Gas Transmission Systems

The growing reliance of electric power systems on gas-fired generation to balance intermittent sources of renewable energy has increased the variation and volume of flows through natural gas transmission pipelines. Adapting pipeline operations to maintain efficiency and security under these new conditions requires optimization methods that account for transients and that can quickly compute solutions in reaction to generator re-dispatch. This paper presents an efficient scheme to minimize compression costs under dynamic conditions where deliveries to customers are described by time-dependent mass flow. The optimization scheme relies on a compact representation of gas flow physics, a trapezoidal discretization in time and space, and a two-stage approach to minimize energy costs and maximize smoothness. The resulting large-scale nonlinear programs are solved using a modern interior-point method. The proposed optimization scheme is validated against an integration of dynamic equations with adaptive time-stepping, as well as a recently proposed state-of-the-art optimal control method. The comparison shows that the solutions are feasible for the continuous problem and also practical from an operational standpoint. The results also indicate that our scheme provides at least an order of magnitude reduction in computation time relative to the state-of-the-art and scales to large gas transmission networks with more than 6000 kilometers of total pipeline

Comparison of three different target blood concentrations of propofol for induction of anaesthesia using target controlled infusion (TCI) technique

We studied three different target blood concentrations (TBC) of propofol for induction of anaesthesia using target controlled infusion (TCI) technique. One hundred and thirty five ASA I and II patients, between 18-55 years of age and undergoing any type of elective surgery were included in the study. All patients were premedicated with oral midazolam 7.5 mg in the ward an hour before induction. Patients were randomly divided into three groups. Group I (n = 45) received initial TBC of 2 J,Jg/ml, group II (n = 45) TBC of 3 J.Jg/ml and group Ill (n = 45) TBC of 4 J,Jg/ml for induction of anaesthesia. Intravenous alfentanil 30 ~g/kg bolus was given as analgesia. Patients were observed for success rate of induction, induction time, effect site concentration and haemodynamic parameters at baseline, 1 minute, 3 minutes and 5 minutes after induction. Success rate of induction was 55.6 %, 86.7% and 91.1 %in group I, 11 and 111 respectively, which showed significant difference only between group I and Ill. Effect site concentration was 0.6 ~g/ml, 0.9 J,Jg/ml and 0.8 JJQ/ml in group I, II and Ill respectively which showed significant difference only between group I and II. There was no significant difference in induction time and haemodynamic parameters among the three groups. Hence, TBC 3 J,Jg/ml was comparable with TBC 4 J.Jg/ml for induction of anaesthesia using TCI technique. However TBC 2 IJQ/ml was not recommended for rapid induction

Optical bistability in sideband output modes induced by squeezed vacuum

We consider $N$ two-level atoms in a ring cavity interacting with a broadband squeezed vacuum centered at frequency $\omega_{s}$ and an input monochromatic driving field at frequency $\omega$. We show that, besides the central mode (at \o), many other {\em sideband modes} are produced at the output, with frequencies shifted from $\omega$ by multiples of $2(\omega -\omega_{s})$. Here we analyze the optical bistability of the two nearest sideband modes, one red-shifted and the other blue-shifted.Comment: Replaced with final published versio