Self-Configuring and Evolving Fuzzy Image Thresholding

Every segmentation algorithm has parameters that need to be adjusted in order to achieve good results. Evolving fuzzy systems for adjustment of segmentation parameters have been proposed recently (Evolving fuzzy image segmentation -- EFIS [1]. However, similar to any other algorithm, EFIS too suffers from a few limitations when used in practice. As a major drawback, EFIS depends on detection of the object of interest for feature calculation, a task that is highly application-dependent. In this paper, a new version of EFIS is proposed to overcome these limitations. The new EFIS, called self-configuring EFIS (SC-EFIS), uses available training data to auto-configure the parameters that are fixed in EFIS. As well, the proposed SC-EFIS relies on a feature selection process that does not require the detection of a region of interest (ROI).Comment: To appear in proceedings of The 14th International Conference on Machine Learning and Applications (IEEE ICMLA 2015), Miami, Florida, USA, 201

An Efficient Parallel Quarter-sweep Point Iterative Algorithm for Solving Poisson Equation on SMP Parallel Computer

A new point iterative algorithm which uses the quarter-sweep approach was shown to be much faster than the full-and half- sweep point iterative algorithms for solving two dimensional Poison equation (Othman el at. 1998». However, the last two algorithms were found to be suitable for parallel implementation (Evans 1984) and Ali el at. (1997». In this paper, the parallel implementation of the new algorithm with the chessboard (CB) strategy on Symmetry Multi Processors (SMP) parallel computer was presented. The experimental results of a test problem were compared with the later two parallel algorithms

Optimization of copper for the improvement of in vitro plant tissue growth of Solanum nigrum

Here was investigated the incorporation of copper in MS medium on growth, and metabolic activities of Solanum nigrum callus. Copper up to 75 µM increased the growth, and thereafter a decline was observed. No considerable alteration in MDA, H2O2, bound phenolics, flavonoids, ascorbate, and copper content was observed with the existence of 25 µM copper, then levels of these parameters were raised with rising copper concentrations. Similarly, 25 µM copper didn't induce a considerable change in lipoxygenase, superoxide dismutase, catalase, peroxidase, phenylalanine ammonia lyase, and polyphenol oxidase activities, however, high levels stimulated these enzymes. Copper at 25 µM didn’t considerably reduce amino acids and soluble proteins, whereas higher concentrations reduced these parameters. Copper treatments reduced the soluble carbohydrates accumulation; only 75 µM enhanced this accumulation. Copper at 25 µM significantly increased the potassium accumulation, whereas higher concentrations reduced this accumulation. From these results, it might be contemplated the optimum effect concerning copper. DOI: http://dx.doi.org/10.5281/zenodo.284864

Recent Advances in Biofuel Cell and Emerging Hybrid System

The present paper reviews the recent development of biofuel cell. Due to its renewable nature and milder operating conditions compared to conventional fuel cell, the electrochemical system has been extensively studied. However, major problems associated with this type of electrochemical system remain an intimidating challenge, the utmost being the low power output and stability of biocatalyst being used. Various attempts have been made to overcome these problems, some are reviewed here. The authors suggest a new direction in solving these problems by using hybrid system i.e. metal biofuel cell. The new hybrid system developed is of lower cost, less complex, higher OCV and greater power output

Network forensics: detection and mitigation of botnet malicious code via darknet

Computer malwares are major threats that always find a way to penetrate the network, posing threats to the confidentiality, integrity and the availability of data. Network-borne malwares penetrate networks by exploiting vulnerabilities in networks and systems. IT administrators in campus wide network continue to look for security control solutions to reduce exposure and magnitude of potential threats. However, with multi-user computers and distributed systems, the campus wide network often becomes a breeding ground for botnets

Design Minkowski Shaped Patch Antenna with Rectangular Parasitic Patch Elements for 5.8 GHz Applications

Abstract—This paper presents the parametric study on the Minkowski shaped antenna with the rectangular parasitic patch elements. This patch antenna consists four parts – patch, feed line, ground plane and parasitic elements. The rectangular parasitic patch elements are located at the bottom of the Minkowski shaped patch. The parametric study of different patch sizes (Design 2A, Design 2B, Design 2C, Design 2D and Design 2E) is presented in this paper. The antenna parameters studied in this paper are resonant frequencies, return loss at the resonant frequency, bandwidth and realized gain. The target frequency of this antenna is 5.80 GHz for Worldwide Interoperability for Microwave Access (WiMAX) application. It shows the return loss of – 24.477 dB, bandwidth of 254 MHz (5.676 GHz to 5.930 GHz) and a gain of 2.351 dB. Index Terms—Minkowski; patch antenna; gain; return loss; bandwidt

Damage Characterization of Polypropylene Honeycomb Sandwich Panels Subjected to Low-Velocity Impact

The post-test deformation and failures of sandwich composites may involve complex interactions between various failure mechanisms. In this study, the extent of impact damages and response of the thermoplastic honeycomb sandwich are analysed through energy profile diagrams and associated load history curves. The degree of the postimpact damages of the sandwich is further characterized using an optical surfaces metrology analysis. The thickness of the honeycomb was found to influence the extent of the damage which occurred following the low-velocity impact. Thicker core was able to sustain a higher load as well as the energy absorption before total failure occurred

RF Front End Receiver for WiMAX Application

This paper presents the design of a high gain, low noise direct conversion Radio frequency(RF) front-end receiver system. The Front end receiver is designed to operate at 5.8 GHz compliant with IEEE 802.16 WIiMAX standard. The system consists of a low noise amplifier (LNA), a radio frequency amplifier (RFA), a power divider and two band pass filters. The overall performance of the RF front-end receiver system produced a gain of 52.4 dB. A cascaded LNA designed for the system produced a high gain of 36.8 dB. The RFA contributed an extra gain 15.6dB. The overall noise figure achieved for the system is 3.7 dB. The return loss achieved is -25.5 dB for the RFA. The radio frequency bandwidth recorded for the system is above 1120 MHz. The measured power divider insertion loss is 2.80 dB. Using microstrip technology for designing the Chebyshev filter, the insertion loss is 3.00 dB and the channel bandwidth recorded is 107 MHz which can accommodate 4 sub channels IEEE WiMAX standard

Neuro-fuzzy systems approach to infill missing rainfall data for Klang River Catchment, Malaysia

Rainfall data can be regarded as the most essential input for various applications in hydrological sciences. Continuous rainfall data with adequate length is the main requirement to solve complex hydrological problems. Mostly in developing countries hydrologists are still facing problems of missing rainfall data with inadequate length. Researchers have been applying a number of statistical and data driven approaches to overcome this insufficiency. This study is an application of neuro-fuzzy system to infill the missing rainfall data for Klang River catchment. Pettitt test, standard normal homogeneity test (SNHT) and Von Neumann Ratio (VNR) tests were performed to check the homogeneity of rainfall data. The neuro-fuzzy model performances were assessed both in calibration and validation stages based on statistical measures such as coefficient of determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). To evaluate the performance of the neuro-fuzzy system model, it was compared with a traditional modeling technique known as autoregressive model with exogenous inputs (ARX). The neuro-fuzzy system model gave better performances in both stages for the best input combinations. The missing rainfall data was predicted using the input combination with best performances. The results of this study showed the effectiveness of the neuro-fuzzy systems and it is recommended as a prominent tool for filling the missing data