A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system

This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

On-Chip Memory Architecture Exploration Framework for DSP Processor-Based Embedded System on Chip

Today's SoCs are complex designs with multiple embedded processors, memory subsystems, and application specific peripherals. The memory architecture of embedded SoCs strongly influences the power and performance of the entire system. Further, the memory subsystem constitutes a major part (typically up to 70%) of the silicon area for the current day SoC. In this article, we address the on-chip memory architecture exploration for DSP processors which are organized as multiple memory banks, where banks can be single/dual ported with non-uniform bank sizes. In this paper we propose two different methods for physical memory architecture exploration and identify the strengths and applicability of these methods in a systematic way. Both methods address the memory architecture exploration for a given target application by considering the application's data access characteristics and generates a set of Pareto-optimal design points that are interesting from a power, performance and VLSI area perspective. To the best of our knowledge, this is the first comprehensive work on memory space exploration at physical memory level that integrates data layout and memory exploration to address the system objectives from both hardware design and application software development perspective. Further we propose an automatic framework that explores the design space identifying 100's of Pareto-optimal design points within a few hours of running on a standard desktop configuration.

Inference for the Component and System Lifetime Distribution of a k-unit Parallel System Based on System Data

In this paper, we consider the inference for the component and system lifetime distribution of a k-unit parallel system with independent components based on system data. The components are assumed to have identical Weibull distribution. We obtain the maximum likelihood estimates of the unknown parameters based on system data. The Fisher information matrix has been derived. We propose -expectation tolerance interval and -content -level tolerance interval for the life distribution of the system. Performance of the estimators and tolerance intervals is investigated via simulation study. A simulated dataset is analyzed for illustration.

A NEAR OPTIMAL PROJECTION FOR SPARSE REPRESENTATION BASED CLASSIFICATION

Sparse representation based classification (SRC) is one of the most successful methods that has been developed in recent times for face recognition. Optimal projection for Sparse representation based classification (OPSRC)1] provides a dimensionality reduction map that is supposed to give optimum performance for SRC framework. However, the computational complexity involved in this method is too high. Here, we propose a new projection technique using the data scatter matrix which is computationally superior to the optimal projection method with comparable classification accuracy with respect OPSRC. The performance of the proposed approach is benchmarked with various publicly available face database.

VISUAL OBJECT TRACKING VIA RANDOM FERNS BASED CLASSIFICATION

Designing a robust algorithm for visual object tracking has been a challenging task since many years. There are trackers in the literature that are reasonably accurate for many tracking scenarios but most of them are computationally expensive. This narrows down their applicability as many tracking applications demand real time response. In this paper, we present a tracker based on random ferns. Tracking is posed as a classification problem and classification is done using ferns. We used ferns as they rely on binary features and are extremely fast at both training and classification as compared to other classification algorithms. Our experiments show that the proposed tracker performs well on some of the most challenging tracking datasets and executes much faster than one of the state-of-the-art trackers, without much difference in tracking accuracy.

Note: A resonating reflector-based optical system for motion measurement in micro-cantilever arrays

A robust, compact optical measurement unit for motion measurement in micro-cantilever arrays enables development of portable micro-cantilever sensors. This paper reports on an optical beam deflection-based system to measure the deflection of micro-cantilevers in an array that employs a single laser source, a single detector, and a resonating reflector to scan the measurement laser across the array. A strategy is also proposed to extract the deflection of individual cantilevers from the acquired data. The proposed system and measurement strategy are experimentally evaluated and demonstrated to measure motion of multiple cantilevers in an array. (C) 2015 AIP Publishing LLC.

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.

Experimental Investigations on the Pulsed Power Switch of a HIRA based UWB System

The Ultra Wide Band (UWB) system has been a subject of research in the last few years due to its utility in various high power electromagnetic applications. Due to its simplicity in design and fabrication, the Half Impulse Radiating Antenna (HIRA) based UWB system has attracted many researchers. Effectiveness of a UWB system, in terms of the bandwidth of the radiated pulse depends on the duration of the radiated field which is typically of sub nanosecond regime. This duration in turn depends on the closure time of the switch used in the UWB pulsed power source. This paper presents the work carried out on the pressurised gas switch of a 50 kV pulsed power system of a HIRA based UWB system. The aim of the present work is to establish the relationship between the pulser switch breakdown voltage and gas pressure, rise time and gas pressure as well as the dependency of the Pulse Repetition Rate (PRR) on the switch breakdown voltage.

HACCP based management system for improving quality of freshwater giant prawn, Macrobrachium rosenbergii

The study was conducted on the present status of HACCP based quality management system of golda, Macrobrachium rosenbergii farms in Fulpur region of Mymensingh. Information was collected on general condition of farms, culture systems and post-harvest quality management. In almost all farms, there is no or inadequate infrastructure facilities such as, road access, electric supply, telecommunications, ice, feed storage facility, vehicle for golda transportation, washing and toilet facilities. The problems associated with sanitation and hygiene was: widespread use of cow dung, poultry manure and construction of open toilet within the vicinity of prawn culture pond. Different grades of commercially available and locally prepared feeds were used for golda culture in the pond. Golda post-larvae (PL) of 40-50 days old were stocked with carp species. The price of golda PL ranged from Tk. 1.00 to Tk. 1.25/piece. The pond size varied from 50 decimal (0.2 ha) to 2.5 acre (1.0 ha) with an average depth of 2-2.5 m. The culture period of golda varied from April-May to November-December and survival rate ranged between 75 and 80%. Production of golda varied from 250-500 kg/acre (625-1,250 kg/ha). Harvested golda were transported to city market within 4 h. Two size grading were generally followed during pricing, e.g. Tk. 500 to 550/kg for >100 g size and Tk. 300/kg for <100 g size. The cost-benefit ratio was found to remain around 1:1.25 depending on availability of PL. Water quality parameters such as, water temperature, pH, dissolved oxygen, total alkalinity and chlorophyll a in five golda farms in Fulpur region were monitored. Water temperature ranged from 29°C to 33°C, dissolved oxygen from 2.28 to 4.13 mg/l, pH between 6.65 and 7.94, alkalinity from 44 to 70 mg/l and chlorophyll a concentration from 61.88 to 102.34 µg/l in the five investigated ponds. The Aerobic Plate Count (APC) of the water sample was within the range of 2.0x10^6 - 2.96x10^7 CFU/ml and of soil samples within the range of 6.9x10^6 - 7.73x10^6 CFU/g. Streptococcus sp., Bacillus sp., Escherichia coli, Staphylococcus sp., Pseudomonas sp. and Salmonella sp. were isolated from pond water and sediment. Different feed samples used for golda was analyzed for proximate composition. Moisture content ranged around 14.14-21.22%, crude protein 20.55-44.1%, lipid 4.67-12.54% and ash 9.7-27.69%. The TVB-N values and peroxide values of feeds used as starter, grower and fish meal were found within the acceptable ranges and samples were free from pathogenic organisms. A training was organized for the golda farmers on HACCP, water quality and post-harvest quality management of prawn.