Search results for: Intrusion Detection Information Exchange
4568 Study on Network-Based Technology for Detecting Potentially Malicious Websites
Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park
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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.
Keywords: Advanced Persistent Threat, Malware, Network Security, Network Packet, Exploit Kits.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15694567 A Model to Study the Effect of Excess Buffers and Na+ Ions on Ca2+ Diffusion in Neuron Cell
Authors: Vikas Tewari, Shivendra Tewari, K. R. Pardasani
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Calcium is a vital second messenger used in signal transduction. Calcium controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and so on. Two theories have been used to simplify the system of reaction-diffusion equations of calcium into a single equation. One is excess buffer approximation (EBA) which assumes that mobile buffer is present in excess and cannot be saturated. The other is rapid buffer approximation (RBA), which assumes that calcium binding to buffer is rapid compared to calcium diffusion rate. In the present work, attempt has been made to develop a model for calcium diffusion under excess buffer approximation in neuron cells. This model incorporates the effect of [Na+] influx on [Ca2+] diffusion,variable calcium and sodium sources, sodium-calcium exchange protein, Sarcolemmal Calcium ATPase pump, sodium and calcium channels. The proposed mathematical model leads to a system of partial differential equations which have been solved numerically using Forward Time Centered Space (FTCS) approach. The numerical results have been used to study the relationships among different types of parameters such as buffer concentration, association rate, calcium permeability.
Keywords: Excess buffer approximation, Na+ influx, sodium calcium exchange protein, sarcolemmal calcium atpase pump, forward time centred space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15994566 Detecting Earnings Management via Statistical and Neural Network Techniques
Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie
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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.Keywords: Earnings management, generalized regression neural networks, linear regression, multi-layer perceptron, Tehran stock exchange.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21064565 Preparation of Sorbent Materials for the Removal of Hardness and Organic Pollutants from Water and Wastewater
Authors: Thanaa Abdel Moghny, Mohamed Keshawy, Mahmoud Fathy, Abdul-Raheim M. Abdul-Raheim, Khalid I. Kabel, Ahmed F. El-Kafrawy, Mahmoud Ahmed Mousa, Ahmed E. Awadallah
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Ecological pollution is of great concern for human health and the environment. Numerous organic and inorganic pollutants usually discharged into the water caused carcinogenic or toxic effect for human and different life form. In this respect, this work aims to treat water contaminated by organic and inorganic waste using sorbent based on polystyrene. Therefore, two different series of adsorbent material were prepared; the first one included the preparation of polymeric sorbent from the reaction of styrene acrylate ester and alkyl acrylate. The second series involved syntheses of composite ion exchange resins of waste polystyrene and amorphous carbon thin film (WPS/ACTF) by solvent evaporation using micro emulsion polymerization. The produced ACTF/WPS nanocomposite was sulfonated to produce cation exchange resins ACTF/WPSS nanocomposite. The sorbents of the first series were characterized using FTIR, 1H NMR, and gel permeation chromatography. The thermal properties of the cross-linked sorbents were investigated using thermogravimetric analysis, and the morphology was characterized by scanning electron microscope (SEM). The removal of organic pollutant was determined through absorption tests in a various organic solvent. The chemical and crystalline structure of nanocomposite of second series has been proven by studies of FTIR spectrum, X-rays, thermal analysis, SEM and TEM analysis to study morphology of resins and ACTF that assembled with polystyrene chain. It is found that the composite resins ACTF/WPSS are thermally stable and show higher chemical stability than ion exchange WPSS resins. The composite resin was evaluated for calcium hardness removal. The result is evident that the ACTF/WPSS composite has more prominent inorganic pollutant removal than WPSS resin. So, we recommend the using of nanocomposite resin as new potential applications for water treatment process.
Keywords: Nanocomposite, sorbent materials, waste water, waste polystyrene.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14074564 Automatic Microaneurysm Quantification for Diabetic Retinopathy Screening
Authors: A. Sopharak, B. Uyyanonvara, S. Barman
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Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.
Keywords: Diabetic retinopathy, microaneurysm, naive Bayes classifier
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21944563 Road Vehicle Recognition Using Magnetic Sensing Feature Extraction and Classification
Authors: Xiao Chen, Xiaoying Kong, Min Xu
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This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.
Keywords: Vehicle classification, signal processing, road traffic model, magnetic sensing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14044562 Multiuser Detection in CDMA Fast Fading Multipath Channel using Heuristic Genetic Algorithms
Authors: Muhammad Naeem, Syed Ismail Shah, Habibullah Jamal
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In this paper, a simple heuristic genetic algorithm is used for Multistage Multiuser detection in fast fading environments. Multipath channels, multiple access interference (MAI) and near far effect cause the performance of the conventional detector to degrade. Heuristic Genetic algorithms, a rapidly growing area of artificial intelligence, uses evolutionary programming for initial search, which not only helps to converge the solution towards near optimal performance efficiently but also at a very low complexity as compared with optimal detector. This holds true for Additive White Gaussian Noise (AWGN) and multipath fading channels. Experimental results are presented to show the superior performance of the proposed techque over the existing methods.Keywords: Genetic Algorithm (GA), Multiple AccessInterference (MAI), Multistage Detectors (MSD), SuccessiveInterference Cancellation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20504561 Taxonomy of Threats and Vulnerabilities in Smart Grid Networks
Authors: Faisal Al Yahmadi, Muhammad R. Ahmed
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Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.
Keywords: Smart grid network, security, threats, vulnerabilities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5994560 Categorical Clustering By Converting Associated Information
Authors: Dongmin Cai, Stephen S-T Yau
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Lacking an inherent “natural" dissimilarity measure between objects in categorical dataset presents special difficulties in clustering analysis. However, each categorical attributes from a given dataset provides natural probability and information in the sense of Shannon. In this paper, we proposed a novel method which heuristically converts categorical attributes to numerical values by exploiting such associated information. We conduct an experimental study with real-life categorical dataset. The experiment demonstrates the effectiveness of our approach.Keywords: Categorical, Clustering, Converting, Information
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13614559 Building a Trend Based Segmentation Method with SVR Model for Stock Turning Detection
Authors: Jheng-Long Wu, Pei-Chann Chang, Yi-Fang Pan
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This research focus on developing a new segmentation method for improving forecasting model which is call trend based segmentation method (TBSM). Generally, the piece-wise linear representation (PLR) can finds some of pair of trading points is well for time series data, but in the complicated stock environment it is not well for stock forecasting because of the stock has more trends of trading. If we consider the trends of trading in stock price for the trading signal which it will improve the precision of forecasting model. Therefore, a TBSM with SVR model used to detect the trading points for various stocks of Taiwanese and America under different trend tendencies. The experimental results show our trading system is more profitable and can be implemented in real time of stock market
Keywords: Trend based segmentation method, support vector machine, turning detection, stock forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31704558 Robust Image Registration Based on an Adaptive Normalized Mutual Information Metric
Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah
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Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.
Keywords: Image registration, mutual information, image gradients, Image transformations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8974557 A Methodological Approach for Detecting Burst Noise in the Time Domain
Authors: Liu Dan, Wang Xue, Wang Guiqin, Qian Zhihong
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The burst noise is a kind of noises that are destructive and frequently found in semiconductor devices and ICs, yet detecting and removing the noise has proved challenging for IC designers or users. According to the properties of burst noise, a methodological approach is presented (proposed) in the paper, by which the burst noise can be analysed and detected in time domain. In this paper, principles and properties of burst noise are expounded first, Afterwards, feasibility (viable) of burst noise detection by means of wavelet transform in the time domain is corroborated in the paper, and the multi-resolution characters of Gaussian noise, burst noise and blurred burst noise are discussed in details by computer emulation. Furthermore, the practical method to decide parameters of wavelet transform is acquired through a great deal of experiment and data statistics. The methodology may yield an expectation in a wide variety of applications.Keywords: Burst noise, detection, wavelet transform
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19134556 Variance Based Component Analysis for Texture Segmentation
Authors: Zeinab Ghasemi, S. Amirhassan Monadjemi, Abbas Vafaei
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This paper presents a comparative analysis of a new unsupervised PCA-based technique for steel plates texture segmentation towards defect detection. The proposed scheme called Variance Based Component Analysis or VBCA employs PCA for feature extraction, applies a feature reduction algorithm based on variance of eigenpictures and classifies the pixels as defective and normal. While the classic PCA uses a clusterer like Kmeans for pixel clustering, VBCA employs thresholding and some post processing operations to label pixels as defective and normal. The experimental results show that proposed algorithm called VBCA is 12.46% more accurate and 78.85% faster than the classic PCA. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19734555 Analysis of Supply Side Factors Affecting Bank Financing of Non-Oil Exports in Nigeria
Authors: Sama’ila Idi Ningi, Abubakar Yusuf Dutse
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The banking sector poses a lot of problems in Nigeria in general and the non-oil export sector in particular. The banks' lack effectiveness in handling small, medium or long-term credit risk (lack of training of loan officers, lack of information on borrowers and absence of a reliable credit registry) results in non-oil exporters being burdened with high requirements, such as up to three years of financial statements, enough collateral to cover both the loan principal and interest (including a cash deposit that may be up to 30% of the loans' net present value), and to provide every detail of the international trade transaction in question. The stated problems triggered this research. Consequently, information on bank financing of non-oil exports was collected from 100 respondents from the 20 Deposit Money Banks (DMBs) in Nigeria. The data was analysed by the use of descriptive statistics correlation and regression. It is found that, Nigerian banks are participants in the financing of non-oil exports. Despite their participation, the rate of interest for credit extended to non-oil export is usually high, ranging between 15-20%. Small and medium sized non-oil export businesses lack the credit history for banks to judge them as reputable. Banks also consider the non-oil export sector very risky for investment. The banks actually do grant less credit than the exporters may require and therefore are not properly funded by banks. Banks grant very low volume of foreign currency loan in addition to, unfavorable exchange rate at which Naira is exchanged to the Dollar and other currencies in the country. This makes importation of inputs costly and negatively impacted on the non-oil export performance in Nigeria.
Keywords: Supply Side Factors, Bank Financing, Non-Oil Exports.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27134554 Investigating what Effects Aviation Fluids Have on the Flatwise Compressive Strength of Nomex® Honeycomb Core Material
Authors: G. Kim, R. Sterkenburg
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One of the disadvantages of honeycomb sandwich structure is that they are prone to fluid intrusion. The purpose of this study is to determine if the structural properties of honeycomb core are affected by contact with a fluid. The test specimens were manufactured of fiberglass prepreg for the facesheets and Nomex® honeycomb core for the core material in accordance with ASTM C-365/365M. Test specimens were soaked in several different kinds of fluids, such as aircraft fuel, turbine engine oil, hydraulic fluid, and water for a period of 60 days. A flatwise compressive test was performed, and the test results were analyzed to determine how the contact with aircraft fluids affected the compressive strength of the Nomex® honeycomb core and how the strength was recovered when the specimens were dry. In addition, the investigation of de-bonding between facesheet and core material after soaking were performed to support the study.
Keywords: Debonding, environmental degradation, honeycomb sandwich structure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6574553 Generalized π-Armendariz Authentication Cryptosystem
Authors: Areej M. Abduldaim, Nadia M. G. Al-Saidi
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Algebra is one of the important fields of mathematics. It concerns with the study and manipulation of mathematical symbols. It also concerns with the study of abstractions such as groups, rings, and fields. Due to the development of these abstractions, it is extended to consider other structures, such as vectors, matrices, and polynomials, which are non-numerical objects. Computer algebra is the implementation of algebraic methods as algorithms and computer programs. Recently, many algebraic cryptosystem protocols are based on non-commutative algebraic structures, such as authentication, key exchange, and encryption-decryption processes are adopted. Cryptography is the science that aimed at sending the information through public channels in such a way that only an authorized recipient can read it. Ring theory is the most attractive category of algebra in the area of cryptography. In this paper, we employ the algebraic structure called skew -Armendariz rings to design a neoteric algorithm for zero knowledge proof. The proposed protocol is established and illustrated through numerical example, and its soundness and completeness are proved.
Keywords: Cryptosystem, identification, skew π-Armendariz rings, skew polynomial rings, zero knowledge protocol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7974552 A Study on the Developing Method of the BIM (Building Information Modeling) Software Based On Cloud Computing Environment
Authors: Byung-Kon Kim
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According as the Architecture, Engineering and Construction (AEC) Industry projects have grown more complex and larger, the number of utilization of BIM for 3D design and simulation is increasing significantly. Therefore, typical applications of BIM such as clash detection and alternative measures based on 3-dimenstional planning are expanded to process management, cost and quantity management, structural analysis, check for regulation, and various domains for virtual design and construction. Presently, commercial BIM software is operated on single-user environment, so initial cost is so high and the investment may be wasted frequently. Cloud computing that is a next-generation internet technology enables simple internet devices (such as PC, Tablet, Smart phone etc) to use services and resources of BIM software. In this paper, we suggested developing method of the BIM software based on cloud computing environment in order to expand utilization of BIM and reduce cost of BIM software. First, for the benchmarking, we surveyed successful case of BIM and cloud computing. And we analyzed needs and opportunities of BIM and cloud computing in AEC Industry. Finally, we suggested main functions of BIM software based on cloud computing environment and developed a simple prototype of cloud computing BIM software for basic BIM model viewing.
Keywords: Construction IT, BIM(Building Information Modeling), Cloud Computing, BIM Service Based Cloud Computing, Viewer Based BIM Server, 3D Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41034551 Numerical Simulation of Fiber Bragg Grating Spectrum for Mode-І Delamination Detection
Authors: O. Hassoon, M. Tarfoui, A. El Malk
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Fiber Bragg optic sensor is embedded in composite material to detect and monitor the damage that occurs in composite structures. In this paper, we deal with the mode-Ι delamination to determine the material strength to crack propagation, using the coupling mode theory and T-matrix method to simulate the FBGs spectrum for both uniform and non-uniform strain distribution. The double cantilever beam test is modeled in FEM to determine the longitudinal strain. Two models are implemented, the first is the global half model, and the second is the sub-model to represent the FBGs with higher refined mesh. This method can simulate damage in composite structures and converting strain to a wavelength shifting in the FBG spectrum.
Keywords: Fiber Bragg grating, Delamination detection, DCB, FBG spectrum, Structure health monitoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 65534550 The Characteristics of a Fair and Efficient Tax Auditing Information System as a Tool against Tax Evasion: A Theoretical Framework
Authors: Dimitris Balios, Stefanos Tantos
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Economic growth and social evolution are connected to trust relationships in a society. The quality of the accounting information, the tax information system and the tax audit mechanism evolve multiple benefits in an economy. Tax evasion, the illegal practice where people and companies do not pay taxes, is a crime because of the negative effect in economy and society. In this paper, we describe a theoretical framework on the characteristics of a fair and efficient tax auditing information system which could be a tool against tax evasion, a tool for an economy to grow, especially in countries that face fluctuations in economic activity. We conclude that a fair and efficient tax auditing information system increases the reliability of tax administration, improves taxpayers’ tax compliance and causes a developmental trajectory for the economy.
Keywords: Auditing information system, auditing mechanism, tax evasion, taxation, quality of accounting information.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11134549 Adaptive Block State Update Method for Separating Background
Authors: Youngsuck Ji, Youngjoon Han, Hernsoo Hahn
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In this paper, we proposed the robust mobile object detection method for light effect in the night street image block based updating reference background model using block state analysis. Experiment image is acquired sequence color video from steady camera. When suddenly appeared artificial illumination, reference background model update this information such as street light, sign light. Generally natural illumination is change by temporal, but artificial illumination is suddenly appearance. So in this paper for exactly detect artificial illumination have 2 state process. First process is compare difference between current image and reference background by block based, it can know changed blocks. Second process is difference between current image-s edge map and reference background image-s edge map, it possible to estimate illumination at any block. This information is possible to exactly detect object, artificial illumination and it was generating reference background more clearly. Block is classified by block-state analysis. Block-state has a 4 state (i.e. transient, stationary, background, artificial illumination). Fig. 1 is show characteristic of block-state respectively [1]. Experimental results show that the presented approach works well in the presence of illumination variance.Keywords: Block-state, Edge component, Reference backgroundi, Artificial illumination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13224548 Defect Detection of Tiles Using 2D-Wavelet Transform and Statistical Features
Authors: M.Ghazvini, S. A. Monadjemi, N. Movahhedinia, K. Jamshidi
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In this article, a method has been offered to classify normal and defective tiles using wavelet transform and artificial neural networks. The proposed algorithm calculates max and min medians as well as the standard deviation and average of detail images obtained from wavelet filters, then comes by feature vectors and attempts to classify the given tile using a Perceptron neural network with a single hidden layer. In this study along with the proposal of using median of optimum points as the basic feature and its comparison with the rest of the statistical features in the wavelet field, the relational advantages of Haar wavelet is investigated. This method has been experimented on a number of various tile designs and in average, it has been valid for over 90% of the cases. Amongst the other advantages, high speed and low calculating load are prominent.Keywords: Defect detection, tile and ceramic quality inspection, wavelet transform, classification, neural networks, statistical features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23804547 Managing User Expectations in Information Systems Development
Authors: Linda, Sau-ling Lai
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This paper provides new ways to explore the old problem of failure of information systems development in an organisation. Based on the theory of cognitive dissonance, information systems (IS) failure is defined as a gap between what the users expect from an information system and how well these expectations are met by the perceived performance of the delivered system. Bridging the expectation-perception gap requires that IS professionals make a radical change from being the proprietor of information systems and products to being service providers. In order to deliver systems and services that IS users perceive as valuable, IS people must become expert in determining and assessing users- expectations and perceptions. It is also suggested that the IS community, in general, has given relatively little attention to the front-end process of requirements specification for IS development. There is a simplistic belief that requirements are obtainable from users, they are then translatable into a formal specification. The process of information needs analysis is problematic and worthy of investigation.Keywords: Information Systems Development, Cognitive Dissonance, Expectation-Perception Gap, Requirements Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36564546 Relation of Optimal Pilot Offsets in the Shifted Constellation-Based Method for the Detection of Pilot Contamination Attacks
Authors: Dimitriya A. Mihaylova, Zlatka V. Valkova-Jarvis, Georgi L. Iliev
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One possible approach for maintaining the security of communication systems relies on Physical Layer Security mechanisms. However, in wireless time division duplex systems, where uplink and downlink channels are reciprocal, the channel estimate procedure is exposed to attacks known as pilot contamination, with the aim of having an enhanced data signal sent to the malicious user. The Shifted 2-N-PSK method involves two random legitimate pilots in the training phase, each of which belongs to a constellation, shifted from the original N-PSK symbols by certain degrees. In this paper, legitimate pilots’ offset values and their influence on the detection capabilities of the Shifted 2-N-PSK method are investigated. As the implementation of the technique depends on the relation between the shift angles rather than their specific values, the optimal interconnection between the two legitimate constellations is investigated. The results show that no regularity exists in the relation between the pilot contamination attacks (PCA) detection probability and the choice of offset values. Therefore, an adversary who aims to obtain the exact offset values can only employ a brute-force attack but the large number of possible combinations for the shifted constellations makes such a type of attack difficult to successfully mount. For this reason, the number of optimal shift value pairs is also studied for both 100% and 98% probabilities of detecting pilot contamination attacks. Although the Shifted 2-N-PSK method has been broadly studied in different signal-to-noise ratio scenarios, in multi-cell systems the interference from the signals in other cells should be also taken into account. Therefore, the inter-cell interference impact on the performance of the method is investigated by means of a large number of simulations. The results show that the detection probability of the Shifted 2-N-PSK decreases inversely to the signal-to-interference-plus-noise ratio.
Keywords: Channel estimation, inter-cell interference, pilot contamination attacks, wireless communications.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6774545 Quality Control of Automotive Gearbox Based On Vibration Signal Analysis
Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri
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In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.Keywords: Automotive gearbox, mathematical morphology, wavelet, bispectrum.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23184544 Photograph Based Pair-matching Recognition of Human Faces
Authors: Min Yao, Kota Aoki, Hiroshi Nagahashi
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In this paper, a novel system recognition of human faces without using face different color photographs is proposed. It mainly in face detection, normalization and recognition. Foot method of combination of Haar-like face determined segmentation and region-based histogram stretchi (RHST) is proposed to achieve more accurate perf using Haar. Apart from an effective angle norm side-face (pose) normalization, which is almost a might be important and beneficial for the prepr introduced. Then histogram-based and photom normalization methods are investigated and ada retinex (ASR) is selected for its satisfactory illumin Finally, weighted multi-block local binary pattern with 3 distance measures is applied for pair-mat Experimental results show its advantageous perfo with PCA and multi-block LBP, based on a principle.Keywords: Face detection, pair-matching rec normalization, skin color segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16004543 Landcover Mapping Using Lidar Data and Aerial Image and Soil Fertility Degradation Assessment for Rice Production Area in Quezon, Nueva Ecija, Philippines
Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto
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Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.
Keywords: Aerial image, land-cover, LiDAR, soil fertility degradation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11434542 Development of a Serial Signal Monitoring Program for Educational Purposes
Authors: Jungho Moon, Lae-Jeong Park
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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.Keywords: Digital sensor, MATLAB, MCU, signal monitoring program.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21154541 Engineering Photodynamic with Radioactive Therapeutic Systems for Sustainable Molecular Polarity: Autopoiesis Systems
Authors: Moustafa Osman Mohammed
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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.
Keywords: Autopoiesis, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8954540 Elephant Herding Optimization for Service Selection in QoS-Aware Web Service Composition
Authors: Samia Sadouki Chibani, Abdelkamel Tari
Abstract:
Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.Keywords: Elephant herding optimization, web service composition, bio-inspired algorithms, QoS optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10324539 Faults Forecasting System
Authors: Hanaa E.Sayed, Hossam A. Gabbar, Shigeji Miyazaki
Abstract:
This paper presents Faults Forecasting System (FFS) that utilizes statistical forecasting techniques in analyzing process variables data in order to forecast faults occurrences. FFS is proposing new idea in detecting faults. Current techniques used in faults detection are based on analyzing the current status of the system variables in order to check if the current status is fault or not. FFS is using forecasting techniques to predict future timing for faults before it happens. Proposed model is applying subset modeling strategy and Bayesian approach in order to decrease dimensionality of the process variables and improve faults forecasting accuracy. A practical experiment, designed and implemented in Okayama University, Japan, is implemented, and the comparison shows that our proposed model is showing high forecasting accuracy and BEFORE-TIME.Keywords: Bayesian Techniques, Faults Detection, Forecasting techniques, Multivariate Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1553