Search results for: mass detection.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2528

Search results for: mass detection.

1868 Fast Algorithm of Infrared Point Target Detection in Fluctuant Background

Authors: Yang Weiping, Zhang Zhilong, Li Jicheng, Chen Zengping, He Jun

Abstract:

The background estimation approach using a small window median filter is presented on the bases of analyzing IR point target, noise and clutter model. After simplifying the two-dimensional filter, a simple method of adopting one-dimensional median filter is illustrated to make estimations of background according to the characteristics of IR scanning system. The adaptive threshold is used to segment canceled image in the background. Experimental results show that the algorithm achieved good performance and satisfy the requirement of big size image-s real-time processing.

Keywords: Point target, background estimation, median filter, adaptive threshold, target detection.

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1867 Real-time Network Anomaly Detection Systems Based on Machine-Learning Algorithms

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

Abstract:

This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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1866 Wormhole Attack Detection in Wireless Sensor Networks

Authors: Zaw Tun, Aung Htein Maw

Abstract:

The nature of wireless ad hoc and sensor networks make them very attractive to attackers. One of the most popular and serious attacks in wireless ad hoc networks is wormhole attack and most proposed protocols to defend against this attack used positioning devices, synchronized clocks, or directional antennas. This paper analyzes the nature of wormhole attack and existing methods of defending mechanism and then proposes round trip time (RTT) and neighbor numbers based wormhole detection mechanism. The consideration of proposed mechanism is the RTT between two successive nodes and those nodes- neighbor number which is needed to compare those values of other successive nodes. The identification of wormhole attacks is based on the two faces. The first consideration is that the transmission time between two wormhole attack affected nodes is considerable higher than that between two normal neighbor nodes. The second detection mechanism is based on the fact that by introducing new links into the network, the adversary increases the number of neighbors of the nodes within its radius. This system does not require any specific hardware, has good performance and little overhead and also does not consume extra energy. The proposed system is designed in ad hoc on-demand distance vector (AODV) routing protocol and analysis and simulations of the proposed system are performed in network simulator (ns-2).

Keywords: AODV, Wormhole attacks, Wireless ad hoc andsensor networks

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1865 Detection of Leaks in Water Mains Using Ground Penetrating Radar

Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi

Abstract:

Ground Penetrating Radar (GPR) is one of the most effective electromagnetic techniques for non-destructive non-invasive subsurface features investigation. Water leak from pipelines is the most common undesirable reason of potable water losses. Rapid detection of such losses is going to enhance the use of the Water Distribution Networks (WDN) and decrease threatens associated with water mains leaks. In this study, GPR approach was developed to detect leaks by implementing an appropriate imaging analyzing strategy based on image refinement, reflection polarity and reflection amplitude that would ease the process of interpreting the collected raw radargram image.

Keywords: Water Networks, Leakage, Water pipelines, Ground Penetrating Radar.

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1864 Envelope-Wavelet Packet Transform for Machine Condition Monitoring

Authors: M. F. Yaqub, I. Gondal, J. Kamruzzaman

Abstract:

Wavelet transform has been extensively used in machine fault diagnosis and prognosis owing to its strength to deal with non-stationary signals. The existing Wavelet transform based schemes for fault diagnosis employ wavelet decomposition of the entire vibration frequency which not only involve huge computational overhead in extracting the features but also increases the dimensionality of the feature vector. This increase in the dimensionality has the tendency to 'over-fit' the training data and could mislead the fault diagnostic model. In this paper a novel technique, envelope wavelet packet transform (EWPT) is proposed in which features are extracted based on wavelet packet transform of the filtered envelope signal rather than the overall vibration signal. It not only reduces the computational overhead in terms of reduced number of wavelet decomposition levels and features but also improves the fault detection accuracy. Analytical expressions are provided for the optimal frequency resolution and decomposition level selection in EWPT. Experimental results with both actual and simulated machine fault data demonstrate significant gain in fault detection ability by EWPT at reduced complexity compared to existing techniques.

Keywords: Envelope Detection, Wavelet Transform, Bearing Faults, Machine Health Monitoring.

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1863 Hydrodynamic Simulation of Co-Current and Counter Current of Column Distillation Using Euler Lagrange Approach

Authors: H. Troudi, M. Ghiss, Z. Tourki, M. Ellejmi

Abstract:

Packed columns of liquefied petroleum gas (LPG) consists of separating the liquid mixture of propane and butane to pure gas components by the distillation phenomenon. The flow of the gas and liquid inside the columns is operated by two ways: The co-current and the counter current operation. Heat, mass and species transfer between phases represent the most important factors that influence the choice between those two operations. In this paper, both processes are discussed using computational CFD simulation through ANSYS-Fluent software. Only 3D half section of the packed column was considered with one packed bed. The packed bed was characterized in our case as a porous media. The simulations were carried out at transient state conditions. A multi-component gas and liquid mixture were used out in the two processes. We utilized the Euler-Lagrange approach in which the gas was treated as a continuum phase and the liquid as a group of dispersed particles. The heat and the mass transfer process was modeled using multi-component droplet evaporation approach. The results show that the counter-current process performs better than the co-current, although such limitations of our approach are noted. This comparison gives accurate results for computations times higher than 2 s, at different gas velocity and at packed bed porosity of 0.9.

Keywords: Co-current, counter current, Euler Lagrange model, heat transfer, mass transfer.

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1862 Multiscale Analysis and Change Detection Based on a Contrario Approach

Authors: F.Katlane, M.S.Naceur, M.A.Loghmari

Abstract:

Automatic methods of detecting changes through satellite imaging are the object of growing interest, especially beca²use of numerous applications linked to analysis of the Earth’s surface or the environment (monitoring vegetation, updating maps, risk management, etc...). This work implemented spatial analysis techniques by using images with different spatial and spectral resolutions on different dates. The work was based on the principle of control charts in order to set the upper and lower limits beyond which a change would be noted. Later, the a contrario approach was used. This was done by testing different thresholds for which the difference calculated between two pixels was significant. Finally, labeled images were considered, giving a particularly low difference which meant that the number of “false changes” could be estimated according to a given limit.

Keywords: multi-scale, a contrario approach, significantthresholds, change detection.

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1861 Predicting Application Layer DDoS Attacks Using Machine Learning Algorithms

Authors: S. Umarani, D. Sharmila

Abstract:

A Distributed Denial of Service (DDoS) attack is a major threat to cyber security. It originates from the network layer or the application layer of compromised/attacker systems which are connected to the network. The impact of this attack ranges from the simple inconvenience to use a particular service to causing major failures at the targeted server. When there is heavy traffic flow to a target server, it is necessary to classify the legitimate access and attacks. In this paper, a novel method is proposed to detect DDoS attacks from the traces of traffic flow. An access matrix is created from the traces. As the access matrix is multi dimensional, Principle Component Analysis (PCA) is used to reduce the attributes used for detection. Two classifiers Naive Bayes and K-Nearest neighborhood are used to classify the traffic as normal or abnormal. The performance of the classifier with PCA selected attributes and actual attributes of access matrix is compared by the detection rate and False Positive Rate (FPR).

Keywords: Distributed Denial of Service (DDoS) attack, Application layer DDoS, DDoS Detection, K- Nearest neighborhood classifier, Naive Bayes Classifier, Principle Component Analysis.

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1860 Design and Fabrication of a Low Cost Heart Monitor using Reflectance Photoplethysmogram

Authors: Nur Ilyani Ramli, Mansour Youseffi, Peter Widdop

Abstract:

This paper presents a low cost design of heart beat monitoring device using reflectance mode PhotoPlethysmography (PPG). PPG is known for its simple construction, ease of use and cost effectiveness and can provide information about the changes in cardiac activity as well as aid in earlier non-invasive diagnostics. The proposed device is divided into three phases. First is the detection of pulses through the fingertip. The signal is then passed to the signal processing unit for the purpose of amplification, filtering and digitizing. Finally the heart rate is calculated and displayed on the computer using parallel port interface. The paper is concluded with prototyping of the device followed by verification procedure of the heartbeat signal obtained in laboratory setting.

Keywords: Reflectance mode PPG, Heart beat detection, Circuitdesign, PCB design

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1859 Improvising Intrusion Detection for Malware Activities on Dual-Stack Network Environment

Authors: Zulkiflee M., Robiah Y., Nur Azman Abu, Shahrin S.

Abstract:

Malware is software which was invented and meant for doing harms on computers. Malware is becoming a significant threat in computer network nowadays. Malware attack is not just only involving financial lost but it can also cause fatal errors which may cost lives in some cases. As new Internet Protocol version 6 (IPv6) emerged, many people believe this protocol could solve most malware propagation issues due to its broader addressing scheme. As IPv6 is still new compares to native IPv4, some transition mechanisms have been introduced to promote smoother migration. Unfortunately, these transition mechanisms allow some malwares to propagate its attack from IPv4 to IPv6 network environment. In this paper, a proof of concept shall be presented in order to show that some existing IPv4 malware detection technique need to be improvised in order to detect malware attack in dual-stack network more efficiently. A testbed of dual-stack network environment has been deployed and some genuine malware have been released to observe their behaviors. The results between these different scenarios will be analyzed and discussed further in term of their behaviors and propagation methods. The results show that malware behave differently on IPv6 from the IPv4 network protocol on the dual-stack network environment. A new detection technique is called for in order to cater this problem in the near future.

Keywords: Dual-Stack, Malware, Worm, IPv6;IDS

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1858 A Distributed Mobile Agent Based on Intrusion Detection System for MANET

Authors: Maad Kamal Al-Anni

Abstract:

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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1857 An Approach for the Prediction of Cardiovascular Diseases

Authors: Nebi Gedik

Abstract:

Regardless of age or gender, cardiovascular illnesses are a serious health concern because of things like poor eating habits, stress, a sedentary lifestyle, hard work schedules, alcohol use, and weight. It tends to happen suddenly and has a high rate of recurrence. Machine learning models can be implemented to assist healthcare systems in the accurate detection and diagnosis of cardiovascular disease (CVD) in patients. Improved heart failure prediction is one of the primary goals of researchers using the heart disease dataset. The purpose of this study is to identify the feature or features that offer the best classification prediction for CVD detection. The support vector machine classifier is used to compare each feature's performance. It has been determined which feature produces the best results.

Keywords: Cardiovascular disease, feature extraction, supervised learning, support vector machine.

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1856 A Distributed Algorithm for Intrinsic Cluster Detection over Large Spatial Data

Authors: Sauravjyoti Sarmah, Rosy Das, Dhruba Kr. Bhattacharyya

Abstract:

Clustering algorithms help to understand the hidden information present in datasets. A dataset may contain intrinsic and nested clusters, the detection of which is of utmost importance. This paper presents a Distributed Grid-based Density Clustering algorithm capable of identifying arbitrary shaped embedded clusters as well as multi-density clusters over large spatial datasets. For handling massive datasets, we implemented our method using a 'sharednothing' architecture where multiple computers are interconnected over a network. Experimental results are reported to establish the superiority of the technique in terms of scale-up, speedup as well as cluster quality.

Keywords: Clustering, Density-based, Grid-based, Adaptive Grid.

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1855 Researches Concerning Photons as Corpuscles with Mass and Negative Electrostatic Charge

Authors: Ioan Rusu

Abstract:

Let us consider that the entire universe is composed of a single hydrogen atom within which the electron is moving around the proton. In this case, according to classical theories of physics, radiation, photons respectively, should be absorbed by the electron. Depending on the number of photons absorbed, the electron radius of rotation around the proton is established. Until now, the principle of photons absorption by electrons and the electron transition to a new energy level, namely to a higher radius of rotation around the proton, is not clarified in physics. This paper aims to demonstrate that radiation, photons respectively, have mass and negative electrostatic charge similar to electrons but infinitely smaller. The experiments which demonstrate this theory are simple: thermal expansion, photoelectric effect and thermonuclear reaction.

Keywords: Electrostatic, electron, proton, photon, radiation.

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1854 Piezoelectric Micro-generator Characterization for Energy Harvesting Application

Authors: José E. Q. Souza, Marcio Fontana, Antonio C. C. Lima

Abstract:

This paper presents analysis and characterization of a piezoelectric micro-generator for energy harvesting application. A low-cost experimental prototype was designed to operate as piezoelectric micro-generator in the laboratory. An input acceleration of 9.8m/s2 using a sine signal (peak-to-peak voltage: 1V, offset voltage: 0V) at frequencies ranging from 10Hz to 160Hz generated a maximum average power of 432.4μW (linear mass position = 25mm) and an average power of 543.3μW (angular mass position = 35°). These promising results show that the prototype can be considered for low consumption load application as an energy harvesting micro-generator.

Keywords: Piezoelectric, microgenerator, energy harvesting, cantilever beam.

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1853 Performance Comparison of Real Time EDAC Systems for Applications On-Board Small Satellites

Authors: Y. Bentoutou

Abstract:

On-board Error Detection and Correction (EDAC) devices aim to secure data transmitted between the central processing unit (CPU) of a satellite onboard computer and its local memory. This paper presents a comparison of the performance of four low complexity EDAC techniques for application in Random Access Memories (RAMs) on-board small satellites. The performance of a newly proposed EDAC architecture is measured and compared with three different EDAC strategies, using the same FPGA technology. A statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in commercial memories onboard Alsat-1 is given for a period of 8 years

Keywords: Error Detection and Correction; On-board computer; small satellite missions

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1852 Efficient Boosting-Based Active Learning for Specific Object Detection Problems

Authors: Thuy Thi Nguyen, Nguyen Dang Binh, Horst Bischof

Abstract:

In this work, we present a novel active learning approach for learning a visual object detection system. Our system is composed of an active learning mechanism as wrapper around a sub-algorithm which implement an online boosting-based learning object detector. In the core is a combination of a bootstrap procedure and a semi automatic learning process based on the online boosting procedure. The idea is to exploit the availability of classifier during learning to automatically label training samples and increasingly improves the classifier. This addresses the issue of reducing labeling effort meanwhile obtain better performance. In addition, we propose a verification process for further improvement of the classifier. The idea is to allow re-update on seen data during learning for stabilizing the detector. The main contribution of this empirical study is a demonstration that active learning based on an online boosting approach trained in this manner can achieve results comparable or even outperform a framework trained in conventional manner using much more labeling effort. Empirical experiments on challenging data set for specific object deteciton problems show the effectiveness of our approach.

Keywords: Computer vision, object detection, online boosting, active learning, labeling complexity.

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1851 Real-Time Fitness Monitoring with MediaPipe

Authors: Chandra Prayaga, Lakshmi Prayaga, Aaron Wade, Kyle Rank, Gopi Shankar Mallu, Sri Satya Harsha Pola

Abstract:

In today's tech-driven world, where connectivity shapes our daily lives, maintaining physical and emotional health is crucial. Athletic trainers play a vital role in optimizing athletes' performance and preventing injuries. However, a shortage of trainers impacts the quality of care. This study introduces a vision-based exercise monitoring system leveraging Google's MediaPipe library for precise tracking of bicep curl exercises and simultaneous posture monitoring. We propose a three-stage methodology: landmark detection, side detection, and angle computation. Our system calculates angles at the elbow, wrist, neck, and torso to assess exercise form. Experimental results demonstrate the system's effectiveness in distinguishing between good and partial repetitions and evaluating body posture during exercises, providing real-time feedback for precise fitness monitoring.

Keywords: Physical health, athletic trainers, fitness monitoring, technology driven solutions, Google's MediaPipe, landmark detection, angle computation, real-time feedback.

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1850 Component-based Segmentation of Words from Handwritten Arabic Text

Authors: Jawad H AlKhateeb, Jianmin Jiang, Jinchang Ren, Stan S Ipson

Abstract:

Efficient preprocessing is very essential for automatic recognition of handwritten documents. In this paper, techniques on segmenting words in handwritten Arabic text are presented. Firstly, connected components (ccs) are extracted, and distances among different components are analyzed. The statistical distribution of this distance is then obtained to determine an optimal threshold for words segmentation. Meanwhile, an improved projection based method is also employed for baseline detection. The proposed method has been successfully tested on IFN/ENIT database consisting of 26459 Arabic words handwritten by 411 different writers, and the results were promising and very encouraging in more accurate detection of the baseline and segmentation of words for further recognition.

Keywords: Arabic OCR, off-line recognition, Baseline estimation, Word segmentation.

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1849 Multiphase Flow Regime Detection Algorithm for Gas-Liquid Interface Using Ultrasonic Pulse-Echo Technique

Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

Abstract:

Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm.

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1848 Anomaly Detection and Characterization to Classify Traffic Anomalies Case Study: TOT Public Company Limited Network

Authors: O. Siriporn, S. Benjawan

Abstract:

This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.

Keywords: Unsupervised, clustering, anomaly, machine learning.

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1847 Heat and Mass Transfer in a Saturated Porous Medium Confined in Cylindrical Annular Geometry

Authors: A. Ja, J. Belabid, A. Cheddadi

Abstract:

This paper reports the numerical simulation of doublediffusive natural convection flows within a horizontal annular filled with a saturated porous medium. The analysis concerns the influence of the different parameters governing the problem, namely, the Rayleigh number Ra, the Lewis number Le and the buoyancy ratio N, on the heat and mass transfer and on the flow structure, in the case of a fixed radius ratio R = 2. The numerical model used for the discretization of the dimensionless equations governing the problem is based on the finite difference method, using the ADI scheme. The study is focused on steady-state solutions in the cooperation situation.

Keywords: Natural convection, double-diffusion, porous medium, annular geometry, finite differences.

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1846 Agrowaste: Phytosterol from Durian Seed

Authors: D. Mohd Nazrul Hisham, J. Mohd Lip, R. Suri, H. Mohamed Shafit, Z.Kharis, K. Shazlin, A. Normah, M.F. Nurul Nabilah

Abstract:

Presence of phytosterol compound in Durian seed (Durio zibethinus) or known as King of fruits has been discovered from screening work using reagent test. Further analysis work has been carried out using mass spectrometer in order to support the priliminary finding. Isolation and purification of the major phytosterol has been carried out using an open column chromatography. The separation was monitored using thin layer chromatography (TLC). Major isolated compounds and purified phytosterol were identified using mass spectrometer and nuclear magnetic resonance (NMR). This novel finding could promote utilization of durian seeds as a functional ingredient in food products through production of standardized extract based on phytosterol content.

Keywords: Agrowaste, durian, seed, phytosterol

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1845 Validation and Application of a New Optimized RP-HPLC-Fluorescent Detection Method for Norfloxacin

Authors: Mahmood Ahmad, Ghulam Murtaza, Sonia Khiljee, Muhammad Asadullah Madni

Abstract:

A new reverse phase-high performance liquid chromatography (RP-HPLC) method with fluorescent detector (FLD) was developed and optimized for Norfloxacin determination in human plasma. Mobile phase specifications, extraction method and excitation and emission wavelengths were varied for optimization. HPLC system contained a reverse phase C18 (5 μm, 4.6 mm×150 mm) column with FLD operated at excitation 330 nm and emission 440 nm. The optimized mobile phase consisted of 14% acetonitrile in buffer solution. The aqueous phase was prepared by mixing 2g of citric acid, 2g sodium acetate and 1 ml of triethylamine in 1 L of Milli-Q water was run at a flow rate of 1.2 mL/min. The standard curve was linear for the range tested (0.156–20 μg/mL) and the coefficient of determination was 0.9978. Aceclofenac sodium was used as internal standard. A detection limit of 0.078 μg/mL was achieved. Run time was set at 10 minutes because retention time of norfloxacin was 0.99 min. which shows the rapidness of this method of analysis. The present assay showed good accuracy, precision and sensitivity for Norfloxacin determination in human plasma with a new internal standard and can be applied pharmacokinetic evaluation of Norfloxacin tablets after oral administration in human.

Keywords: Norfloxacin, Aceclofenac sodium, Methodoptimization, RP-HPLC method, Fluorescent detection, Calibrationcurve.

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1844 Dispersion Rate of Spilled Oil in Water Column under Non-Breaking Water Waves

Authors: Hanifeh Imanian, Morteza Kolahdoozan

Abstract:

The purpose of this study is to present a mathematical phrase for calculating the dispersion rate of spilled oil in water column under non-breaking waves. In this regard, a multiphase numerical model is applied for which waves and oil phase were computed concurrently, and accuracy of its hydraulic calculations have been proven. More than 200 various scenarios of oil spilling in wave waters were simulated using the multiphase numerical model and its outcome were collected in a database. The recorded results were investigated to identify the major parameters affected vertical oil dispersion and finally 6 parameters were identified as main independent factors. Furthermore, some statistical tests were conducted to identify any relationship between the dependent variable (dispersed oil mass in the water column) and independent variables (water wave specifications containing height, length and wave period and spilled oil characteristics including density, viscosity and spilled oil mass). Finally, a mathematical-statistical relationship is proposed to predict dispersed oil in marine waters. To verify the proposed relationship, a laboratory example available in the literature was selected. Oil mass rate penetrated in water body computed by statistical regression was in accordance with experimental data was predicted. On this occasion, it was necessary to verify the proposed mathematical phrase. In a selected laboratory case available in the literature, mass oil rate penetrated in water body computed by suggested regression. Results showed good agreement with experimental data. The validated mathematical-statistical phrase is a useful tool for oil dispersion prediction in oil spill events in marine areas.

Keywords: Dispersion, marine environment, mathematical-statistical relationship, oil spill.

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1843 Segmentation of Ascending and Descending Aorta in CTA Images

Authors: H. Özkan

Abstract:

In this study, a new and fast algorithm for Ascending Aorta (AscA) and Descending Aorta (DesA) segmentation is presented using Computed Tomography Angiography images. This process is quite important especially at the detection of aortic plaques, aneurysms, calcification or stenosis. The applied method has been carried out at four steps. At first step, lung segmentation is achieved. At the second one, Mediastinum Region (MR) is detected to use in the segmentation. At the third one, images have been applied optimal threshold and components which are outside of the MR were removed. Lastly, identifying and segmentation of AscA and DesA have been carried out. The performance of the applied method is found quite well for radiologists and it gives enough results to the surgeries medically.

Keywords: Ascending aorta (AscA), Descending aorta (DesA), Computed tomography angiography (CTA), Computer aided detection (CAD), Segmentation

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1842 Moving towards Positive Security Model for Web Application Firewall

Authors: Asrul H. Yaacob, Nazrul M. Ahmad, Nurul N. Ahmad, Mardeni Roslee

Abstract:

The proliferation of web application and the pervasiveness of mobile technology make web-based attacks even more attractive and even easier to launch. Web Application Firewall (WAF) is an intermediate tool between web server and users that provides comprehensive protection for web application. WAF is a negative security model where the detection and prevention mechanisms are based on predefined or user-defined attack signatures and patterns. However, WAF alone is not adequate to offer best defensive system against web vulnerabilities that are increasing in number and complexity daily. This paper presents a methodology to automatically design a positive security based model which identifies and allows only legitimate web queries. The paper shows a true positive rate of more than 90% can be achieved.

Keywords: Intrusion Detection System, Positive Security Model, Web application Firewall

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1841 A Preliminary Study on Effects of Community Structures on Epidemic Spreading and Detection in Complex Networks

Authors: Yi Yu, Gaoxi Xiao

Abstract:

Community structures widely exist in almost all real-life networks. Extensive researches have been carried out on detecting community structures in complex networks. However, many aspects of how community structures may affect the dynamics and properties of complex networks still remain unclear. In this work, we examine the impacts of community structures on the epidemic spreading and detection in complex networks. Extensive simulation results show that community structures may not help decrease the infection size at steady state, yet they could indeed help slow down the infection spreading. Also, networks with strong community structures may expect to have a smaller average infection size when equipped with a number of sparsely deployed monitors.

Keywords: Complex network, epidemic spreading, infection size, infection monitoring.

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1840 Effect of Chromium Behavior on Mechanical and Electrical Properties of P/M Copper-Chromium Alloy Dispersed with VGCF

Authors: Hisashi Imai, Kuan-Yu Chen, Katsuyoshi Kondoh, Hung-Yin Tsai, Junko Umeda

Abstract:

Microstructural and electrical properties of Cu-chromium alloy (Cu-Cr) dispersed with vapor-grown carbon fiber (VGCF) prepared by powder metallurgy (P/M) process have been investigated. Cu-0.7 mass% Cr pre-alloyed powder (Cu-Cr) made by water atomization process was used as raw materials, which contained solid solute Cr elements in Cu matrix. The alloy powder coated with un-bundled VGCF by using oil coating process was consolidated at 1223 K in vacuum by spark plasma sintering, and then extruded at 1073 K. The extruded Cu-Cr alloy (monolithic alloy) had 209.3 MPa YS and 80.4 IACS% conductivity. The extruded Cu-Cr with 0.1 mass% VGCF composites revealed a small decrease of YS compared to the monolithic Cu-Cr alloy. On the other hand, the composite had a higher electrical conductivity than that of the monolithic alloy. For example, Cu-Cr with 0.1 mass% VGCF composite sintered for 5 h showed 182.7 MPa YS and 89.7 IACS% conductivity. In the case of Cu-Cr with VGCFs composites, the Cr concentration was observed around VGCF by SEM-EDS analysis, where Cr23C6 compounds were detected by TEM observation. The amount of Cr solid solution in the matrix of the Cu-Cr composites alloy was about 50% compared to the monolithic Cu-Cr sintered alloy, and resulted in the remarkable increment of the electrical conductivity.

Keywords: Powder metallurgy Cu-Cr alloy powder, vapor-grown carbon fiber, electrical conductivity.

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1839 Bearing Fault Feature Extraction by Recurrence Quantification Analysis

Authors: V. G. Rajesh, M. V. Rajesh

Abstract:

In rotating machinery one of the critical components that is prone to premature failure is the rolling bearing. Consequently, early warning of an imminent bearing failure is much critical to the safety and reliability of any high speed rotating machines. This study is concerned with the application of Recurrence Quantification Analysis (RQA) in fault detection of rolling element bearings in rotating machinery. Based on the results from this study it is reported that the RQA variable, percent determinism, is sensitive to the type of fault investigated and therefore can provide useful information on bearing damage in rolling element bearings.

Keywords: Bearing fault detection, machine vibrations, nonlinear time series analysis, recurrence quantification analysis.

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