Search results for: cefoxitin disc diffusion MRSA detection

Authors: M. Okeke, A. Blyth

Abstract:

Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

Procedia PDF Downloads 301

Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

Procedia PDF Downloads 520

Authors: Muhammad Hassan Khalil, Xu Jiadong

Abstract:

Detection of malignant tumor inside the breast of women is a challenging field for the researchers. MWI (Microwave imaging) for breast cancer diagnosis has been of interest for last two decades, newly it suggested for finding cancerous tissues of women breast. A simple and basic idea of the mathematical modeling is used throughout this paper for imaging of malignant tumor. In this paper, the authors explained inverse scattering method in the microwave imaging and also present some simulation results.

Keywords: breast cancer detection, microwave imaging, tomography, tumor

Procedia PDF Downloads 411

Authors: Mohammad Esmaeilpour

Abstract:

One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes.

Keywords: magnetic resonance neuroimaging, subtle change detection and quantification, algebraic decomposition, basis functions

Procedia PDF Downloads 474

Authors: Sally Salah El Menshawy, Ghada M. Ahmed GabAllah, Doaa Khedr M. Khedr

Abstract:

Background: Our study aims to detect the diagnostic role of DTI in the differentiation of salivary glands benign and malignant lesions. Results: Our study included 50 patients (25males and 25 females) divided into 4 groups (benign lesions n=20, malignant tumors n=13, post-operative changes n=10 and normal n=7). 28 patients were with parotid gland lesions, 4 patients were with submandibular gland lesions and only 1 case with sublingual gland affection. The mean fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of malignant salivary gland tumors (n = 13) (0.380±0.082 and 0.877±0.234× 10⁻³ mm² s⁻¹) were significantly different (P<0.001) than that of benign tumors (n = 20) (0.147±0.03 and 1.47±0.605 × 10⁻³ mm² s⁻¹), respectively. The mean FA and ADC of post-operative changes (n = 10) were (0.211±0.069 and 1.63±0.20× 10⁻³ mm² s⁻¹) while that of normal glands (n =7) was (0.251±0.034and 1.54±0.29× 10⁻³ mm² s⁻¹), respectively. Using ADC to differentiate malignant lesions from benign lesions has an (AUC) of 0.810, with an accuracy of 69.7%. ADC used to differentiate malignant lesions from post-operative changes has (AUC) of 1.0, and an accuracy of 95.7%. FA used to discriminate malignant from benign lesions has (AUC) of 1.0, and an accuracy of 93.9%. FA used to differentiate malignant from post-operative changes has (AUC) of 0.923, and an accuracy of 95.7%. Combined FA and ADC used to differentiate malignant from benign lesions has (AUC) of 1.0, and an accuracy of 100%. Combined FA and ADC used to differentiate malignant from post-operative changes has (AUC) of 1.0, and an accuracy of 100%. Conclusion: Combined FA and ADC can differentiate malignant tumors from benign salivary gland lesions.

Keywords: diffusion tensor imaging, MRI, salivary gland, tumors

Procedia PDF Downloads 111

Authors: Prikhil Agrawal, N. Priyanka

Abstract:

With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

Procedia PDF Downloads 297

Authors: Ahlem Abid, Farah Jemili

Abstract:

Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

Procedia PDF Downloads 147

Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

Abstract:

In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

Procedia PDF Downloads 380

Authors: Amer Dawoud, Jesy Motchaalangaram, Arati Biswakarma, Wujan Mio, Karl Wallace

Abstract:

The development of an embedded miniaturized drone-based system for remote detection of Chemical Warfare Agents (CWA) is proposed. The paper focuses on the software/hardware system design of the electrochemical Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) signal processing for future deployment on drones. The paper summarizes the progress made towards hardware and electrochemical signal processing for signature detection of CWA. Also, the miniature potentiostat signal is validated by comparing it with the high-end lab potentiostat signal.

Keywords: drone-based, remote detection chemical warfare agents, miniaturized, potentiostat

Procedia PDF Downloads 136

Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

Abstract:

Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

Procedia PDF Downloads 269

Authors: Mohammad Ghiasvand, Babak Khorsandi, Morteza Kolahdoozan

Abstract:

Under the influence of waves, oil in the sea is subject to vertical scattering in the water column. Scientists' knowledge of how oil is dispersed in the water column is one of the lowest levels of knowledge among other processes affecting oil in the marine environment, which highlights the need for research and study in this field. Therefore, this study investigates the distribution of oil in the water column in a turbulent environment with zero velocity characteristics. Lack of laboratory results to analyze the distribution of petroleum pollutants in deep water for information Phenomenon physics on the one hand and using them to calibrate numerical models on the other hand led to the development of laboratory models in research. According to the aim of the present study, which is to investigate the distribution of oil in homogeneous and isotropic turbulence caused by the oscillating Grid, after reaching the ideal conditions, the crude oil flow was poured onto the water surface and oil was distributed in deep water due to turbulence was investigated. In this study, all experimental processes have been implemented and used for the first time in Iran, and the study of oil diffusion in the water column was considered one of the key aspects of pollutant diffusion in the oscillating Grid environment. Finally, the required oscillation velocities were taken at depths of 10, 15, 20, and 25 cm from the water surface and used in the analysis of oil diffusion due to turbulence parameters. The results showed that with the characteristics of the present system in two static modes and network motion with a frequency of 0.8 Hz, the results of oil diffusion in the four mentioned depths at a frequency of 0.8 Hz compared to the static mode from top to bottom at 26.18, 57 31.5, 37.5 and 50% more. Also, after 2.5 minutes of the oil spill at a frequency of 0.8 Hz, oil distribution at the mentioned depths increased by 49, 61.5, 85, and 146.1%, respectively, compared to the base (static) state.

Keywords: homogeneous and isotropic turbulence, oil distribution, oscillating grid, oil spill

Procedia PDF Downloads 75

Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

Abstract:

In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

Procedia PDF Downloads 216

Authors: Mahmut Yildirim

Abstract:

This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

Procedia PDF Downloads 72

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

Abstract:

The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

Procedia PDF Downloads 137

Authors: Jianrong Wu, Xuan Fu, Akihiro Higashi, Zhiming Tan

Abstract:

CMOS image sensors with a rolling shutter are used broadly in the digital cameras embedded in mobile devices. The rolling shutter suffers the flicker artifacts from the fluorescent lamp, and it could be observed easily. In this paper, the characteristics of illumination flicker in motion case were analyzed, and two efficient detection methods based on matching fragment selection were proposed. According to the experimental results, our methods could achieve as high as 100% accuracy in static scene, and at least 97% in motion scene.

Keywords: illumination flicker, embedded camera, rolling shutter, detection

Procedia PDF Downloads 420

Authors: R. Rezaeipour, A. R. Mehrabi

Abstract:

Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results.

Keywords: fault location detection, active distribution system, micro grids, network operators

Procedia PDF Downloads 789

Authors: Zhongfei Cai, Hui He, Changsheng Li

Abstract:

This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

Procedia PDF Downloads 340

Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

Abstract:

Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

Procedia PDF Downloads 62

Authors: M. Ardelean, F. Manea, A. Pop, J. Schoonman

Abstract:

The presence of pharmaceuticals in the environment and especially in water has gained increasing attention. They are included in emerging class of pollutants, and for most of them, legal limits have not been set-up due to their impact on human health and ecosystem was not determined and/or there is not the advanced analytical method for their quantification. In this context, the development of various advanced analytical methods for the quantification of pharmaceuticals in water is required. The electrochemical methods are known to exhibit the great potential for high-performance analytical methods but their performance is in direct relation to the electrode material and the operating techniques. In this study, two types of carbon-based electrodes materials, i.e., boron-doped diamond (BDD) and carbon nanofiber (CNF)-epoxy composite electrodes have been investigated through voltammetric techniques for the detection of naproxen in water. The comparative electrochemical behavior of naproxen (NPX) on both BDD and CNF electrodes was studied by cyclic voltammetry, and the well-defined peak corresponding to NPX oxidation was found for each electrode. NPX oxidation occurred on BDD electrode at the potential value of about +1.4 V/SCE (saturated calomel electrode) and at about +1.2 V/SCE for CNF electrode. The sensitivities for NPX detection were similar for both carbon-based electrode and thus, CNF electrode exhibited superiority in relation to the detection potential. Differential-pulsed voltammetry (DPV) and square-wave voltammetry (SWV) techniques were exploited to improve the electroanalytical performance for the NPX detection, and the best results related to the sensitivity of 9.959 µA·µM^-1 were achieved using DPV. In addition, the simultaneous detection of NPX and fluoxetine -a very common antidepressive drug, also present in water, was studied using CNF electrode and very good results were obtained. The detection potential values that allowed a good separation of the detection signals together with the good sensitivities were appropriate for the simultaneous detection of both tested pharmaceuticals. These results reclaim CNF electrode as a valuable tool for the individual/simultaneous detection of pharmaceuticals in water.

Keywords: boron-doped diamond electrode, carbon nanofiber-epoxy composite electrode, emerging pollutans, pharmaceuticals

Procedia PDF Downloads 281

Authors: Surena V.

Abstract:

Background and Aim: Periodontal diseases are among the most common infectious diseases all around the world, even in developed countries. Considering the increased rate of microbial resistance to antibiotics and the chemical side effects of antibiotics and antiseptics used for the treatment of periodontal disease, there is a need for an alternative antimicrobial agent with fewer complications. Medicinal herbs have recently become popular as antimicrobial and preventive agents. This study aimed to assess the antibacterial effects of hydroalcoholic extracts of Lawsonia inermis, Malva sylvestris and Boswellia serrata on Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans). Materials and Methods: Hydroalcoholic extracts of the three medicinal plants were obtained by the maceration technique and A. actinomycetemcomitans was cultured. The antimicrobial efficacy of the three medicinal plants was compared with that of 0.2% chlorhexidine (CHX) according to the CLSI protocol using agar disc diffusion and broth microdilution techniques. All tests were repeated three times. Results: Hydroalcoholic extracts of all three plants had antimicrobial activity against A. actinomycetemcomitans. The minimum inhibitory concentration (MIC) of Lawsonia inermis, Malva sylvestris, and Boswellia serrata was 78.1, 156.2, and 1666 µg/mL with no significant difference between them. The MIC of CHX was 3.33 µg/mL, which was significantly higher than that of Boswellia serrata extract. Conclusion: Given that, further in vivo studies confirm other properties of these extracts and their safety in terms of cytotoxicity and mutagenicity, hydroalcoholic extracts of Lawsonia inermis and Malva sylvestris may be used in mouthwashes or local delivery systems to affect periodontal biofilm.

Keywords: actinobacilus actinomycetem commitans, lawsonia inermis, malva sylvestris, boswellia serrata

Procedia PDF Downloads 59

Authors: A. Sacko, H. Nyoni, T. A. M. Msagati, B. Ntsendwana

Abstract:

Carbon based materials to target environmental pollutants have become increasingly recognized in science. Electrochemical methods using carbon based materials are notable methods for high sensitive detection of organic pollutants in air. It is therefore in this light that exfoliated graphite electrode was fabricated for electrochemical analysis of PAHs in urban atmospheric air. The electrochemical properties of the graphite electrode were studied using CV and EIS in the presence of acetate buffer supporting electrolyte with 2 Mm ferricyanide as a redox probe. The graphite electrode showed enhanced current response which confirms facile kinetics and enhanced sensitivity. However, the peak to peak (DE) separation increased as a function of scan rate. The EIS showed a high charger transfer resistance. The detection phenanthrene on the exfoliated graphite was studied in the presence of acetate buffer solution at PH 3.5 using DPV. The oxidation peak of phenanthrene was observed at 0.4 V. Under optimized conditions (supporting electrolyte, pH, deposition time, etc.). The detection limit observed was at 5x 10⁻⁸ M. Thus the results demonstrate with further optimization and modification lower concentration detection can be achieved.

Keywords: electrochemical detection, exfoliated graphite, PAHs (polycyclic aromatic hydrocarbons), urban air

Procedia PDF Downloads 204

Authors: Muhammad Arshad, Ghulam Hussain Bhatti, Abdul Qayyum

Abstract:

Zinc-doped silica oxide nanoparticles having size 7.93nm were synthesized by the deposition precipitation method by using different solvents (acetonitrile, n-hexane, isoamylalchol). Biological potential such as antibacterial activities against Bacillussubtilusand Escherichia coli, and antifungal activities against Candida parapsilosis and Aspergilusniger were also investigated by Disc diffusion method. Different characterizations techniques including Fournier Transmission Infrared Spectroscopy (FT-IR), X-ray diffraction (XRD), Scanning Electron Microscope (SEM), Transmission Electron Microscope (TEM), Thermo-gravimeteric Analysis (TGA), Atomic forced microscopy (AFM), and Dynamic Light Scattering (DLS) were used. FT-IR characterization confirmed the presence of metal oxide bond (SiO2) while XRD showed the hexagonal structure. SEM and TEM characterization showed the morphology of nanoparticles. AFM study showed good particle size distribution as depicted by a histogram. DLS study showed the gradual decease in the size of nanoparticles from 24.86nm to 13.24 nm. Highest antibacterial activities revealed by acetonitrile solvents (6%and 4.5%) followed by isoamylalchol (3% and 2.4%) while n-hexane solvent showed the lowest activity (2%and 1%) respectively. Higher antifungal activities exhibited by n-hexane (0.34 % and 0.43%) followed by isoamylalchol (0.27% and 0.19%) solvent while acetonitrile (0.21% and 0.17%) showed least activity respectively. Statistical analysis by using one-way ANOVA also indicated the significant results of both biological activities.

Keywords: nanoparticles, precipitation methods, antibacterial, antifungal, characterizations

Procedia PDF Downloads 207

Authors: Yu-Kuei Hsu, Yan-Gu Lin

Abstract:

A facile and simple fabrication of copper(II) oxide (CuO) nanosheet on copper foil as nanoelectrode for H2O2 sensing application was proposed in this study. The spontaneous formation of CuO nanosheets by immersing the copper foil into 0.1 M NaOH aqueous solution for 48 hrs was carried out at room temperature. The sheet-like morphology with several ten nanometers in thickness and ~500 nm in width was observed by SEM. Those nanosheets were confirmed the monoclinic-phase CuO by the structural analysis of XRD and Raman spectra. The directly grown CuO nanosheets film is mechanically stable and offers an excellent electrochemical sensing platform. The CuO nanosheets electrode shows excellent electrocatalytic response to H2O2 with significantly lower overpotentials for its oxidation and reduction and also exhibits a fast response and high sensitivity for the amperometric detection of H2O2. The novel spontaneously grown CuO nanosheets electrode is readily applicable to other analytes and has great potential applications in the electrochemical detection.

Keywords: CuO, nanosheets, H2O2 detection, Cu foil

Procedia PDF Downloads 289

Authors: Belete B. Beyene, Ayenew M. Mihirteu, Misganaw T. Ayana, Amogne W. Yibeltal

Abstract:

Modification of synthetic porphyrins is one of the promising strategies in an attempt to get molecules with desired properties and applications. Here in, we report synthesis, photophysical characterization and antibacterial activity of 5, 10, 15, 20-tetrakis-(4- methoxy carbonyl phenyl) porphyrin M(II); where M = Co, Fe, Ni, Zn. Metallation of the ligand was confirmed by using UV–Vis spectroscopy and ESI-Ms measurement, in which the number of Q bands in absorption spectra of the ligand decreased from four to one or two as a result of metal insertion to the porphyrin core. The antibacterial activity study of the complexes toward two Gram-positive (Staphylococcus aureus (S. aureus) and Streptococcus pyogenes (s. pyogenes)) and two Gram-negative (Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae)) bacteria by disc diffusion method showed a promising inhibitory activity. The complexes exhibited highest activities at highest concentration and were better than the activity of free base ligand, the salts, and blank solution. This could be explained on the basis of Overton's concept of cell permeability and Tweed's Chelation theory. An increased lipo-solubility enhances the penetration of the complexes into the lipid membrane and interferes with the normal activities of the bacteria. Our study, therefore, showed that the growth inhibitory effect of these metalloporphyrins is generally in order of ZnTPPCOOMe > NiTPPCOOMe > CoTPPCOOMe> FeTPPCOOMe, which may be attributed to the better lipophilicity and binding of the complex with the cellular components.

Keywords: porphyrins, metalloporphyrins, spectral property, antibacterial activity, synthesis

Procedia PDF Downloads 72

Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

Abstract:

Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

Procedia PDF Downloads 478

Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

Abstract:

Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

Procedia PDF Downloads 119

Authors: Radka Pernicova

Abstract:

Chloride resistance in Ultra High Performance Concrete (UHPC) is determined in this paper. This work deals with the one dimension chloride transport, which can be potentially dangerous particularly for the durability of concrete structures. Risk of reinforcement corrosion due to exposure to the concrete surface to direct the action of chloride ions (mainly in the form de-icing salts or groundwater) is dangerously increases. The measured data are investigated depending on the depth of penetration of chloride ions into the concrete structure. Comparative measurements with normal strength concrete are done as well. The experimental results showed that UHCP have improved resistance of chlorides penetration than NSC and also chloride diffusion depth is significantly lower in UHCP.

Keywords: chloride, one dimensional diffusion, transport, salinity, UHPC

Procedia PDF Downloads 435

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. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. 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, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.

Keywords: Integral differential equations, , L-stable methods, pricing European options, Jump–diffusion model

Procedia PDF Downloads 151

Authors: Mehmet Fahri Sarac, Gokcen Akgun

Abstract:

Ti–6Al–4V alloys are widely used in biomedical industries because of its attractive mechanical and physicochemical properties. However, they have poor wear resistance. High velocity oxygen fuel (HVOF) coatings were investigated as a way to improve the wear resistance of this alloy. In this paper, different mass ratio of Al₂O₃-TiO₂ powders (60/40, 87/13 and 97/3) was employed to enhance the tribological properties of Ti–6Al–4V. The tribological behavior was investigated by wear tests using ball-on-disc and pin-on-disc tribometer. The microstructures of the contact surfaces were determined by a scanning electron microscopy before and after the test to study the wear mechanism. Uncoated and coated surfaces after wear test are also subjected to micro-hardness tests. The tribological test results showed that the microhardness, friction and wear resistance of coated Ti-6Al-4V alloys increases by increasing TiO₂ content in the powder composite when other experimental conditions were constant. Finally, Al₂O₃-TiO₂ powder composites for the investigated conditions, both coating samples had satisfactory values of friction and wear resistance, and they could be suitable candidates for Ti–6Al–4V material.

Keywords: HVOF (High Velocity Oxygen Fuel), Al₂O₃-TiO₂, Ti-6Al-4V, tribology

Procedia PDF Downloads 195

Authors: Ahmadu Maidorawa, Idrissa Djibo, Muhammad Tella

Abstract:

This paper presents a method for detecting flow chart and figure plagiarism based on shape of image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets. Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offense that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide these checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts result in look holes that people can take advantage. That means people can plagiarize figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts.

Keywords: flowchart, multimedia retrieval, figures similarity, image comparison, figure retrieval

Procedia PDF Downloads 464