Search results for: cefoxitin disc diffusion MRSA detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4819

Search results for: cefoxitin disc diffusion MRSA detection

4429 Phytochemial Screening, Anti-Microbial and Mineral Determination of Brysocarpus coccineus Root

Authors: I. L. Ibrahim, A. Mann, A. Ndanaimi

Abstract:

The research involved phytochemical screening, antibacterial activities and mineral determination by flame photometry of the crude extract of Brysocarpus coccineus schum indeed were carried out. The result of Phytochemical screening reveal tha saponins, alkaloids, cardiac glycosides, and anthraquinones were present. This suggests that the plant extract could be used as anti-inflammatory and anti-bleeding agents. Estimation of mineral content shows that the crude extract of B. coccineus contains 0.73 (Na+), 1.06 (K+) and 1.98 (Ca+) which justifies its use to be safe for hypertensive patients and could be used to lower blood pressure. The antibacterial properties of aqueous and ethanol extract were studied against some bacteria; pseudomonas aeruginosa, Escherichia coli, Bacilus subtilis, Klebsilla penmuoniae by disc diffusion method. The aqueous extract showed significant activity against the organisms while the ethanol at concentrations 5-10mg/ml ethanol extract showed significant zone of inhibition against the organisms, E. coli, (19 mm), B. cereus (12 mm), P. aeruginosa (11 mm), K. pnemuoniae (11 mm). Minimum inhibitory concentration (MIC) was carried with considerable effect of inhibition on the organisms. The MIC values observed were 1, 24, 16 and 19 mm against E. coli, B. cereus, P. aeruginosa and K. pnemuoniae respectively. Therefore, the plant could be a potential source of antibacterial agent although more pharmacological and clinical study may be recommended.

Keywords: phytochemicals, microorganisms, screenings, mineral ions

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4428 Bayesian Prospective Detection of Small Area Health Anomalies Using Kullback Leibler Divergence

Authors: Chawarat Rotejanaprasert, Andrew Lawson

Abstract:

Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

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4427 Roof Material Detection Based on Object-Based Approach Using WorldView-2 Satellite Imagery

Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

Abstract:

One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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4426 Approaches for Minimizing Radioactive Tritium and ¹⁴C in Advanced High Temperature Gas-Cooled Reactors

Authors: Longkui Zhu, Zhengcao Li

Abstract:

High temperature gas-cooled reactors (HTGRs) are considered as one of the next-generation advanced nuclear reactors, in which porous nuclear graphite is used as neutron moderators, reflectors, structure materials, and cooled by inert helium. Radioactive tritium and ¹⁴C are generated in terms of reactions of thermal neutrons and ⁶Li, ¹⁴N, ¹⁰B impurely within nuclear graphite and the coolant during HTGRs operation. Currently, hydrogen and nitrogen diffusion behavior together with nuclear graphite microstructure evolution were investigated to minimize the radioactive waste release, using thermogravimetric analysis, X-ray computed tomography, the BET and mercury standard porosimetry methods. It is found that the peak value of graphite weight loss emerged at 573-673 K owing to nitrogen diffusion from graphite pores to outside when the system was subjected to vacuum. Macropore volume became larger while porosity for mesopores was smaller with temperature ranging from ambient temperature to 1073 K, which was primarily induced by coalescence of the subscale pores. It is suggested that the porous nuclear graphite should be first subjected to vacuum at 573-673 K to minimize the nitrogen and the radioactive 14°C before operation in HTGRs. Then, results on hydrogen diffusion show that the diffusible hydrogen and tritium could permeate into the coolant with diffusion coefficients of > 0.5 × 10⁻⁴ cm²·s⁻¹ at 50 bar. As a consequence, the freshly-generated diffusible tritium could release quickly to outside once formed, and an effective approach for minimizing the amount of radioactive tritium is to make the impurity contents extremely low in nuclear graphite and the coolant. Besides, both two- and three-dimensional observations indicate that macro and mesopore volume along with total porosity decreased with temperature at 50 bar on account of synergistic effects of applied compression strain, sharpened pore morphology, and non-uniform temperature distribution.

Keywords: advanced high temperature gas-cooled reactor, hydrogen and nitrogen diffusion, microstructure evolution, nuclear graphite, radioactive waste management

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4425 Phytochemial Screening, Anti-Microbial, and Minerals Determination of Leptadenia Hastata

Authors: I. L. Ibrahim, A. Mann, B. A. Adam

Abstract:

This project involved screening for antibacterial activity, phytochemical and mineral properties of Leptadenia hastata by flame photometry. The result of phytochemical screening reveals that the presence of flavonoids, tannins, saponins, alkaloids, steroidal, and anthraquinones while the cardiac glycoside was absent. This justifies the plant been used as anti-bleeding and anti-inflammatory agents. The result of flame photometry revealed that 1.85 % (Na), 0.65% (K) and 1.85 % (Ca) which indicates the safe nature of the plant extract as such could be used to lower high blood pressure. The antibacterial properties of both the aqueous and ethanolic extract were studied against some bacteria, Escherichia coli, Bacillus Cercus, Pseudomonas aeruginas, and Enterobacter aerogegens, by disc diffusion method and the result reveals that there are very good activities against the organism while the ethanolic extract at concentration 1.0 – 1.2 mg/ml. the ethanolic extract showed in considerable zone inhibition against bacteria’s; Escherichia coli, Bacillus Cercus, pseudomonas aeruginosa andklebsellapnemuoniae. Minimum inhibitory concentration (MIC) and minimum Bacterial concentration (MBC) were conducted with fairly good significant effect of inhibition on the organism, therefore, plant extract could be a potential source of antibacterial agent.

Keywords: antibacterial activity, Leptadenia hastata, infectious diseases, phytochemical screening

Procedia PDF Downloads 588
4424 Robust Numerical Scheme for Pricing American Options under Jump Diffusion Models

Authors: Salah Alrabeei, Mohammad Yousuf

Abstract:

The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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4423 Machine Learning Approach for Anomaly Detection in the Simulated Iec-60870-5-104 Traffic

Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

Abstract:

Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

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4422 Overview and Future Opportunities of Sarcasm Detection on Social Media Communications

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

Abstract:

Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

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4421 Developing Artificial Neural Networks (ANN) for Falls Detection

Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

Abstract:

The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

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4420 Investigation of Doping Effects on Nonradiative Recombination Parameters in Bulk GaAs

Authors: Soufiene Ilahi

Abstract:

We have used Photothermal deflection spectroscopy PTD to investigate the impact of doping on electronics properties of bulk. Then, the extraction of these parameters is performed by fitting the theoretical curves to the experimental PTD ones. We have remarked that electron mobility in p type C-doped GaAs is about 300 cm2/V·s. Accordinagly, the diffusion length of minority carrier lifetime is equal to 5 (± 7%), 5 (± 4,4%) and 1.42 µm (± 7,2 %) for the Cr, C and Si doped GaAs respectively. Surface recombination velocity varies randomly that can be found around of 7942 m/s, 100 m/s and 153 m/s GaAs doped Si, Cr, C, respectively.

Keywords: nonradiative lifetime, mobility of minority carrier, diffusion length, surface and interface recombination in GaAs

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4419 Multiscale Edge Detection Based on Nonsubsampled Contourlet Transform

Authors: Enqing Chen, Jianbo Wang

Abstract:

It is well known that the wavelet transform provides a very effective framework for multiscale edges analysis. However, wavelets are not very effective in representing images containing distributed discontinuities such as edges. In this paper, we propose a novel multiscale edge detection method in nonsubsampled contourlet transform (NSCT) domain, which is based on the dominant multiscale, multidirection edge expression and outstanding edge location of NSCT. Through real images experiments, simulation results demonstrate that the proposed method is better than other edge detection methods based on Canny operator, wavelet and contourlet. Additionally, the proposed method also works well for noisy images.

Keywords: edge detection, NSCT, shift invariant, modulus maxima

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4418 Evaluation of Differential Interaction between Flavanols and Saliva Proteins by Diffusion and Precipitation Assays on Cellulose Membranes

Authors: E. Obreque-Slier, V. Contreras-Cortez, R. López-Solís

Abstract:

Astringency is a drying, roughing, and sometimes puckering sensation that is experienced on the various oral surfaces during or immediately after tasting foods. This sensation has been closely related to the interaction and precipitation between salivary proteins and polyphenols, specifically flavanols or proanthocyanidins. In addition, the type and concentration of proanthocyanidin influences significantly the intensity of the astringency and consequently the protein/proanthocyanidin interaction. However, most of the studies are based on the interaction between saliva and highly complex polyphenols, without considering the effect of monomeric proanthoancyanidins present in different foods. The aim of this study was to evaluate the effect of different monomeric proanthocyanidins on the diffusion and precipitation of salivary proteins. Thus, solutions of catechin, epicatechin, epigallocatechin and gallocatechin (0, 2.0, 4.0, 6.0, 8.0 and 10 mg/mL) were mixed with human saliva (1: 1 v/v). After incubation for 5 min at room temperature, 15 µL aliquots of each mix were dotted on a cellulose membrane and allowed to dry spontaneously at room temperature. The membrane was fixed, rinsed and stained for proteins with Coomassie blue. After exhaustive washing in 7% acetic acid, the membrane was rinsed once in distilled water and dried under a heat lamp. Both diffusion area and stain intensity of the protein spots were semiqualitative estimates for protein-tannin interaction (diffusion test). The rest of the whole saliva-phenol solution mixtures of the diffusion assay were centrifuged, and 15-μL aliquots from each of the supernatants were dotted on a cellulose membrane. The membrane was processed for protein staining as indicated above. The blue-stained area of protein distribution corresponding to each of the extract dilution-saliva mixtures was quantified by Image J 1.45 software. Each of the assays was performed at least three times. Initially, salivary proteins display a biphasic distribution on cellulose membranes, that is, when aliquots of saliva are placed on absorbing cellulose membranes, and free diffusion of saliva is allowed to occur, a non-diffusible protein fraction becomes surrounded by highly diffusible salivary proteins. In effect, once diffusion has ended, a protein-binding dye shows an intense blue-stained roughly circular area close to the spotting site (non-diffusible fraction) (NDF) which becomes surrounded by a weaker blue-stained outer band (diffusible fraction) (DF). Likewise, the diffusion test showed that epicatechin caused the complete disappearance of DF from saliva with 2 mg/mL. Also, epigallocatechin and gallocatechin caused a similar effect with 4 mg/mL, while catechin generated the same effect at 8 mg/mL. In the precipitation test, the use of epicatechin and gallocatechin generated evident precipitates at the bottom of the Eppendorf tubes. In summary, the flavanol type differentially affects the diffusion and precipitation of saliva, which would affect the sensation of astringency perceived by consumers.

Keywords: astringency, polyphenols, tannins, tannin-protein interaction

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4417 Implementation of Edge Detection Based on Autofluorescence Endoscopic Image of Field Programmable Gate Array

Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

Abstract:

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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4416 Detection of Nanotoxic Material Using DNA Based QCM

Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

Abstract:

Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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4415 The Status of BIM Adoption in Six Continents

Authors: Wooyoung Jung, Ghang Lee

Abstract:

This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

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4414 Detection of Epinephrine in Chicken Serum at Iron Oxide Screen Print Modified Electrode

Authors: Oluwole Opeyemi Dina, Saheed E. Elugoke, Peter Olutope Fayemi, Omolola E. Fayemi

Abstract:

This study presents the detection of epinephrine (EP) at Fe₃O₄ modified screen printed silver electrode (SPSE). The iron oxide (Fe₃O₄) nanoparticles were characterized with UV-visible spectroscopy, Fourier-Transform infrared spectroscopy (FT-IR) and Scanning electron microscopy (SEM) prior to the modification of the SPSE. The EP oxidation peak current (Iap) increased with an increase in the concentration of EP as well as the scan rate (from 25 - 400 mVs⁻¹). Using cyclic voltammetry (CV), the relationship between Iap and EP concentration was linear over a range of 3.8 -118.9 µM and 118.9-175 µM with a detection limit of 41.99 µM and 83.16 µM, respectively. Selective detection of EP in the presence of ascorbic acid was also achieved at this electrode.

Keywords: screenprint electrode, iron oxide nanoparticle, epinephrine, serum, cyclic voltametry

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4413 Same-Day Detection Method of Salmonella Spp., Shigella Spp. and Listeria Monocytogenes with Fluorescence-Based Triplex Real-Time PCR

Authors: Ergun Sakalar, Kubra Bilgic

Abstract:

Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

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4412 Latency-Based Motion Detection in Spiking Neural Networks

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

Abstract:

Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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4411 Gray Level Image Encryption

Authors: Roza Afarin, Saeed Mozaffari

Abstract:

The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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4410 Inverter IGBT Open–Circuit Fault Detection Using Park's Vectors Enhanced by Polar Coordinates

Authors: Bendiabdellah Azzeddine, Cherif Bilal Djamal Eddine

Abstract:

The three-phase power converter voltage structure is widely used in many power applications but its failure can lead to partial or total loss of control of the phase currents and can cause serious system malfunctions or even a complete system shutdown. To ensure continuity of service in all circumstances, effective and rapid techniques of detection and location of inverter fault is to be implemented. The present paper is dedicated to open-circuit fault detection in a three-phase two-level inverter fed induction motor. For detection purpose, the proposed contribution addresses the Park’s current vectors associated to a polar coordinates calculation tool to compute the exact value of the fault angle corresponding directly to the faulty IGBT switch. The merit of the proposed contribution is illustrated by experimental results.

Keywords: diagnosis, detection, Park’s vectors, polar coordinates, open-circuit fault, inverter, IGBT switch

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4409 Aminopeptidase P (DAP) Expression Pattern in Drosophila Melanogaster

Authors: Suneeta Gireesh Panicker

Abstract:

Aim: Aminopeptidase P (APP) is an enzyme that has specificity for proline, can specifically cleave Xaa-Proline peptides and is a metallo-aminopeptidase. The bonds nearby to the imino acid proline are tough to cleave by many peptidases, but APP can specifically break peptide bonds engaged with proline. Membrane-bound form and a cytosolic form are the two forms in which this enzyme exists. The exact physiological function of APP remains unclear and hence the present work attempts to determine it. Methods: In the present study, the expression pattern of cytosolic Aminopeptidase P (DAP) was determined in all the embryonic stages and larval stages of wild-type Drosophila by using polyclonal monospecific antibodies. To show the presence of DAP RNA in embryonic and larval stages, RNA in situ hybridization was performed. DAP promoter-LacZ fusion reporter gene vector was used to construct transgenic embryos to study the regulation pattern of DAP. To study the DAP expression profile, a transgenic fly consisting of a DAP promoter with β-gal and GFP reporter genes in front of it was constructed. Results: DAP protein expression was observed in neuroectodermal cells, posterior midgut primordium, proctodeum, ventral neuroblast and primordial stomatogastric nervous system. It was observed in the ventral cord and midgut in stage 12. The completely developed embryos showed the intense occurrence of it in the ventral cord and gut region. The eye-antennal disc, wing disc and leg disc also showed the presence of DAP protein. LacZ expression in transgenic embryos also showed the same pattern. Conclusion: Similar to various known multiple-functional proteins, DAP could be one with different functions at different stages and in different cells. Data presented here designates DAP functions in the early embryonic and imaginal dics differentiation and development, suggesting that it may be required for the metabolism of proteins like neuropeptides and tachykinins.

Keywords: aminopeptidase P, in situ hybridization, transgenic fly, embryonic stages

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4408 Comparative Analysis of Edge Detection Techniques for Extracting Characters

Authors: Rana Gill, Chandandeep Kaur

Abstract:

Segmentation of images can be implemented using different fundamental algorithms like edge detection (discontinuity based segmentation), region growing (similarity based segmentation), iterative thresholding method. A comprehensive literature review relevant to the study gives description of different techniques for vehicle number plate detection and edge detection techniques widely used on different types of images. This research work is based on edge detection techniques and calculating threshold on the basis of five edge operators. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny. Segmentation of characters present in different type of images like vehicle number plate, name plate of house and characters on different sign boards are selected as a case study in this work. The proposed methodology has seven stages. The proposed system has been implemented using MATLAB R2010a. Comparison of all the five operators has been done on the basis of their performance. From the results it is found that Canny operators produce best results among the used operators and performance of different edge operators in decreasing order is: Canny>Log>Sobel>Prewitt>Roberts.

Keywords: segmentation, edge detection, text, extracting characters

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4407 A Dynamic Ensemble Learning Approach for Online Anomaly Detection in Alibaba Datacenters

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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4406 Medical Image Watermark and Tamper Detection Using Constant Correlation Spread Spectrum Watermarking

Authors: Peter U. Eze, P. Udaya, Robin J. Evans

Abstract:

Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

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4405 Tracking of Intramuscular Stem Cells by Magnetic Resonance Diffusion Weighted Imaging

Authors: Balakrishna Shetty

Abstract:

Introduction: Stem Cell Imaging is a challenging field since the advent of Stem Cell treatment in humans. Series of research on tagging and tracking the stem cells has not been very effective. The present study is an effort by the authors to track the stem cells injected into calf muscles by Magnetic Resonance Diffusion Weighted Imaging. Materials and methods: Stem Cell injection deep into the calf muscles of patients with peripheral vascular disease is one of the recent treatment modalities followed in our institution. 5 patients who underwent deep intramuscular injection of stem cells as treatment were included for this study. Pre and two hours Post injection MRI of bilateral calf regions was done using 1.5 T Philips Achieva, 16 channel system using 16 channel torso coils. Axial STIR, Axial Diffusion weighted images with b=0 and b=1000 values with back ground suppression (DWIBS sequence of Philips MR Imaging Systems) were obtained at 5 mm interval covering the entire calf. The invert images were obtained for better visualization. 120ml of autologous bone marrow derived stem cells were processed and enriched under c-GMP conditions and reduced to 40ml solution containing mixture of above stem cells. Approximately 40 to 50 injections, each containing 0.75ml of processed stem cells, was injected with marked grids over the calf region. Around 40 injections, each of 1ml normal saline, is injected into contralateral leg as control. Results: Significant Diffusion hyper intensity is noted at the site of injected stem cells. No hyper intensity noted before the injection and also in the control side where saline was injected conclusion: This is one of the earliest studies in literature showing diffusion hyper intensity in intramuscularly injected stem cells. The advantages and deficiencies in this study will be discussed during the presentation.

Keywords: stem cells, imaging, DWI, peripheral vascular disease

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4404 A Microfluidic Biosensor for Detection of EGFR 19 Deletion Mutation Targeting Non-Small Cell Lung Cancer on Rolling Circle Amplification

Authors: Ji Su Kim, Bo Ram Choi, Ju Yeon Cho, Hyukjin Lee

Abstract:

Epidermal growth factor receptor (EGFR) 19 deletion mutation gene is over-expressed in carcinoma patient. EGFR 19 deletion mutation is known as typical biomarker of non-small cell lung cancer (NSCLC), which one section in the coding exon 19 of EGFR is deleted. Therefore, there have been many attempts over the years to detect EGFR 19 deletion mutation for replacing conventional diagnostic method such as PCR and tissue biopsy. We developed a simple and facile detection platform based on Rolling Circle Amplification (RCA), which provides highly amplified products in isothermal amplification of the ligated DNA template. Limit of detection (~50 nM) and a faster detection time (~30 min) could be achieved by introducing RCA.

Keywords: EGFR19, cancer, diagnosis, rolling circle amplification (RCA), hydrogel

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4403 Feedforward Neural Network with Backpropagation for Epilepsy Seizure Detection

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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4402 Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images

Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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4401 Biologically Inspired Small Infrared Target Detection Using Local Contrast Mechanisms

Authors: Tian Xia, Yuan Yan Tang

Abstract:

In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

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4400 Cognitive Methods for Detecting Deception During the Criminal Investigation Process

Authors: Laid Fekih

Abstract:

Background: It is difficult to detect lying, deception, and misrepresentation just by looking at verbal or non-verbal expression during the criminal investigation process, as there is a common belief that it is possible to tell whether a person is lying or telling the truth just by looking at the way they act or behave. The process of detecting lies and deception during the criminal investigation process needs more studies and research to overcome the difficulties facing the investigators. Method: The present study aimed to identify the effectiveness of cognitive methods and techniques in detecting deception during the criminal investigation. It adopted the quasi-experimental method and covered a sample of (20) defendants distributed randomly into two homogeneous groups, an experimental group of (10) defendants be subject to criminal investigation by applying cognitive techniques to detect deception and a second experimental group of (10) defendants be subject to the direct investigation method. The tool that used is a guided interview based on models of investigative questions according to the cognitive deception detection approach, which consists of three techniques of Vrij: imposing the cognitive burden, encouragement to provide more information, and ask unexpected questions, and the Direct Investigation Method. Results: Results revealed a significant difference between the two groups in term of lie detection accuracy in favour of defendants be subject to criminal investigation by applying cognitive techniques, the cognitive deception detection approach produced superior total accuracy rates both with human observers and through an analysis of objective criteria. The cognitive deception detection approach produced superior accuracy results in truth detection: 71%, deception detection: 70% compared to a direct investigation method truth detection: 52%; deception detection: 49%. Conclusion: The study recommended if practitioners use a cognitive deception detection technique, they will correctly classify more individuals than when they use a direct investigation method.

Keywords: the cognitive lie detection approach, deception, criminal investigation, mental health

Procedia PDF Downloads 66