Search results for: AI algorithm internal audit
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4127

Search results for: AI algorithm internal audit

2297 An Exploration of Cross-Cultural Behaviour: The Characteristics of Chinese Consumers’ Decision Making in Europe

Authors: Yongsheng Guo, Xiaoxian Zhu, Mandella Osei-Assibey Bonsu

Abstract:

This study explores the effects of national culture on consumer behaviour by identifying the characteristics of Chinese consumers’ decision making in Europe. It offers a better understanding of how cultural factors affect consumers’ behaviour, and how consumers make decisions in other nations with different culture. It adopted a grounded theory approach and conducted 24 in-depth interviews. Grounded theory models are developed to link the causal conditions, process, and consequences. Results reveal that some cultural factors including conservatism, emotionality, acquaintance community, long-term orientation and principles affect Chinese consumers when making purchase decisions in Europe. Most Chinese consumers plan and prepare their expenditure and stay in Europe as cultural learners, and purchase durable products or assets as investment, and share their experiences within a community. This study identified potential problems such as political and social environment, complex procedures, and restrictions. This study found that external factors influence internal factors and then internal characters determine consumer behaviour. This study proposes that cultural traits developed in convergence evolution through social selection and Chinese consumers persist most characters but adapt some perceptions and actions overtime in other countries. This study suggests that cultural marketing could be adopted by companies to reflect consumers’ preferences. Agencies, shops, and the authorities could take actions to reduce the complexity and restrictions.

Keywords: National culture, consumer behaviour, cultural marketing, decision making.

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2296 MATLAB/SIMULINK Based Model of Single- Machine Infinite-Bus with TCSC for Stability Studies and Tuning Employing GA

Authors: Sidhartha Panda, Narayana Prasad Padhy

Abstract:

With constraints on data availability and for study of power system stability it is adequate to model the synchronous generator with field circuit and one equivalent damper on q-axis known as the model 1.1. This paper presents a systematic procedure for modelling and simulation of a single-machine infinite-bus power system installed with a thyristor controlled series compensator (TCSC) where the synchronous generator is represented by model 1.1, so that impact of TCSC on power system stability can be more reasonably evaluated. The model of the example power system is developed using MATLAB/SIMULINK which can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, the parameters of the TCSC controller are optimized using genetic algorithm. The non-linear simulation results are presented to validate the effectiveness of the proposed approach.

Keywords: Genetic algorithm, MATLAB/SIMULINK, modelling and simulation, power system stability, single-machineinfinite-bus power system, thyristor controlled series compensator.

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2295 Efficient Large Numbers Karatsuba-Ofman Multiplier Designs for Embedded Systems

Authors: M.Machhout, M.Zeghid, W.El hadj youssef, B.Bouallegue, A.Baganne, R.Tourki

Abstract:

Long number multiplications (n ≥ 128-bit) are a primitive in most cryptosystems. They can be performed better by using Karatsuba-Ofman technique. This algorithm is easy to parallelize on workstation network and on distributed memory, and it-s known as the practical method of choice. Multiplying long numbers using Karatsuba-Ofman algorithm is fast but is highly recursive. In this paper, we propose different designs of implementing Karatsuba-Ofman multiplier. A mixture of sequential and combinational system design techniques involving pipelining is applied to our proposed designs. Multiplying large numbers can be adapted flexibly to time, area and power criteria. Computationally and occupation constrained in embedded systems such as: smart cards, mobile phones..., multiplication of finite field elements can be achieved more efficiently. The proposed designs are compared to other existing techniques. Mathematical models (Area (n), Delay (n)) of our proposed designs are also elaborated and evaluated on different FPGAs devices.

Keywords: finite field, Karatsuba-Ofman, long numbers, multiplication, mathematical model, recursivity.

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2294 Estimation of Systolic and Diastolic Pressure using the Pulse Transit Time

Authors: Soo-young Ye, Gi-Ryon Kim, Dong-Keun Jung, Seong-wan Baik, Gye-rok Jeon

Abstract:

In this paper, algorithm estimating the blood pressure was proposed using the pulse transit time (PTT) as a more convenient method of measuring the blood pressure. After measuring ECG and pressure pulse, and photoplethysmography, the PTT was calculated from the acquired signals. Thereafter, the system to indirectly measure the systolic pressure and the diastolic pressure was composed using the statistic method. In comparison between the blood pressure indirectly measured by proposed algorithm estimating the blood pressure and real blood pressure measured by conventional sphygmomanometer, the systolic pressure indicates the mean error of ±3.24mmHg and the standard deviation of 2.53mmHg, while the diastolic pressure indicates the satisfactory result, that is, the mean error of ±1.80mmHg and the standard deviation of 1.39mmHg. These results are satisfied with the regulation of ANSI/AAMI for certification of sphygmomanometer that real measurement error value should be within the mean error of ±5mmHg and the standard deviation of 8mmHg. These results are suggest the possibility of applying to portable and long time blood pressure monitoring system hereafter.

Keywords: Blood pressure, Systolic, Diastolic, Pulse transit time.

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2293 Optimized Data Fusion in an Intelligent Integrated GPS/INS System Using Genetic Algorithm

Authors: Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas

Abstract:

Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites- outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.

Keywords: Adaptive Network based Fuzzy Inference System (ANFIS), Genetic optimization, Global Positioning System (GPS), Inertial Navigation System (INS).

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2292 Low Energy Method for Data Delivery in Ubiquitous Network

Authors: Tae Kyung Kim, Hee Suk Seo

Abstract:

Recent advances in wireless sensor networks have led to many routing methods designed for energy-efficiency in wireless sensor networks. Despite that many routing methods have been proposed in USN, a single routing method cannot be energy-efficient if the environment of the ubiquitous sensor network varies. We present the controlling network access to various hosts and the services they offer, rather than on securing them one by one with a network security model. When ubiquitous sensor networks are deployed in hostile environments, an adversary may compromise some sensor nodes and use them to inject false sensing reports. False reports can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. The interleaved hop-by-hop authentication scheme detects such false reports through interleaved authentication. This paper presents a LMDD (Low energy method for data delivery) algorithm that provides energy-efficiency by dynamically changing protocols installed at the sensor nodes. The algorithm changes protocols based on the output of the fuzzy logic which is the fitness level of the protocols for the environment.

Keywords: Data delivery, routing, simulation.

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2291 The Tag Authentication Scheme using Self-Shrinking Generator on RFID System

Authors: HangRok Lee, DoWon Hong

Abstract:

Since communications between tag and reader in RFID system are by radio, anyone can access the tag and obtain its any information. And a tag always replies with the same ID so that it is hard to distinguish between a real and a fake tag. Thus, there are many security problems in today-s RFID System. Firstly, unauthorized reader can easily read the ID information of any Tag. Secondly, Adversary can easily cheat the legitimate reader using the collected Tag ID information, such as the any legitimate Tag. These security problems can be typically solved by encryption of messages transmitted between Tag and Reader and by authentication for Tag. In this paper, to solve these security problems on RFID system, we propose the Tag Authentication Scheme based on self shrinking generator (SSG). SSG Algorithm using in our scheme is proposed by W.Meier and O.Staffelbach in EUROCRYPT-94. This Algorithm is organized that only one LFSR and selection logic in order to generate random stream. Thus it is optimized to implement the hardware logic on devices with extremely limited resource, and the output generating from SSG at each time do role as random stream so that it is allow our to design the light-weight authentication scheme with security against some network attacks. Therefore, we propose the novel tag authentication scheme which use SSG to encrypt the Tag-ID transmitted from tag to reader and achieve authentication of tag.

Keywords: RFID system, RFID security, self shrinkinggeneratior, authentication, protocol.

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2290 Fast Intra Prediction Algorithm for H.264/AVC Based on Quadratic and Gradient Model

Authors: A. Elyousfi, A. Tamtaoui, E. Bouyakhf

Abstract:

The H.264/AVC standard uses an intra prediction, 9 directional modes for 4x4 luma blocks and 8x8 luma blocks, 4 directional modes for 16x16 macroblock and 8x8 chroma blocks, respectively. It means that, for a macroblock, it has to perform 736 different RDO calculation before a best RDO modes is determined. With this Multiple intra-mode prediction, intra coding of H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standards, but computational complexity is increased significantly. This paper presents a fast intra prediction algorithm for H.264/AVC intra prediction based a characteristic of homogeneity information. In this study, the gradient prediction method used to predict the homogeneous area and the quadratic prediction function used to predict the nonhomogeneous area. Based on the correlation between the homogeneity and block size, the smaller block is predicted by gradient prediction and quadratic prediction, so the bigger block is predicted by gradient prediction. Experimental results are presented to show that the proposed method reduce the complexity by up to 76.07% maintaining the similar PSNR quality with about 1.94%bit rate increase in average.

Keywords: Intra prediction, H.264/AVC, video coding, encodercomplexity.

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2289 Beam Orientation Optimization Using Ant Colony Optimization in Intensity Modulated Radiation Therapy

Authors: Xi Pei, Ruifen Cao, Hui Liu, Chufeng Jin, Mengyun Cheng, Huaqing Zheng, Yican Wu, FDS Team

Abstract:

In intensity modulated radiation therapy (IMRT) treatment planning, beam angles are usually preselected on the basis of experience and intuition. Therefore, getting an appropriate beam configuration needs a very long time. Based on the present situation, the paper puts forward beam orientation optimization using ant colony optimization (ACO). We use ant colony optimization to select the beam configurations, after getting the beam configuration using Conjugate Gradient (CG) algorithm to optimize the intensity profiles. Combining with the information of the effect of pencil beam, we can get the global optimal solution accelerating. In order to verify the feasibility of the presented method, a simulated and clinical case was tested, compared with dose-volume histogram and isodose line between target area and organ at risk. The results showed that the effect was improved after optimizing beam configurations. The optimization approach could make treatment planning meet clinical requirements more efficiently, so it had extensive application perspective.

Keywords: intensity modulated radiation therapy, ant colonyoptimization, Conjugate Gradient algorithm

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2288 Optimal Control Strategy for High Performance EV Interior Permanent Magnet Synchronous Motor

Authors: Mehdi Karbalaye Zadeh, Ehsan M. Siavashi

Abstract:

The controllable electrical loss which consists of the copper loss and iron loss can be minimized by the optimal control of the armature current vector. The control algorithm of current vector minimizing the electrical loss is proposed and the optimal current vector can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to the experimental PM motor drive system and this paper presents a modern approach of speed control for permanent magnet synchronous motor (PMSM) applied for Electric Vehicle using a nonlinear control. The regulation algorithms are based on the feedback linearization technique. The direct component of the current is controlled to be zero which insures the maximum torque operation. The near unity power factor operation is also achieved. More over, among EV-s motor electric propulsion features, the energy efficiency is a basic characteristic that is influenced by vehicle dynamics and system architecture. For this reason, the EV dynamics are taken into account.

Keywords: PMSM, Electric Vehicle, Optimal control, Traction.

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2287 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

Abstract:

Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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2286 Image Contrast Enhancement based Sub-histogram Equalization Technique without Over-equalization Noise

Authors: Hyunsup Yoon, Youngjoon Han, Hernsoo Hahn

Abstract:

In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.

Keywords: Contrast Enhancement, Histogram Equalization, Histogram Region Equalization, Equalization Noise

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2285 Two States Mapping Based Neural Network Model for Decreasing of Prediction Residual Error

Authors: Insung Jung, lockjo Koo, Gi-Nam Wang

Abstract:

The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.

Keywords: Neural network, U-healthcare, prediction, timeseries, computer aided prediction.

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2284 Design and Implementation of Secure Electronic Payment System (Client)

Authors: Pyae Pyae Hun

Abstract:

Secure electronic payment system is presented in this paper. This electronic payment system is to be secure for clients such as customers and shop owners. The security architecture of the system is designed by RC5 encryption / decryption algorithm. This eliminates the fraud that occurs today with stolen credit card numbers. The symmetric key cryptosystem RC5 can protect conventional transaction data such as account numbers, amount and other information. This process can be done electronically using RC5 encryption / decryption program written by Microsoft Visual Basic 6.0. There is no danger of any data sent within the system being intercepted, and replaced. The alternative is to use the existing network, and to encrypt all data transmissions. The system with encryption is acceptably secure, but that the level of encryption has to be stepped up, as computing power increases. Results In order to be secure the system the communication between modules is encrypted using symmetric key cryptosystem RC5. The system will use simple user name, password, user ID, user type and cipher authentication mechanism for identification, when the user first enters the system. It is the most common method of authentication in most computer system.

Keywords: A 128-bit block cipher, Microsoft visual basic 6.0, RC5 encryption /decryption algorithm and TCP/IP protocol.

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2283 Offline Parameter Identification and State-of-Charge Estimation for Healthy and Aged Electric Vehicle Batteries Based on the Combined Model

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: Lithium-Ion batteries, genetic algorithm optimization, battery aging test, and parameter identification.

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2282 An Energy-Efficient Distributed Unequal Clustering Protocol for Wireless Sensor Networks

Authors: Sungju Lee, Jangsoo Lee , Hongjoong Sin, Seunghwan Yoo, Sanghyuck Lee, Jaesik Lee, Yongjun Lee, Sungchun Kim

Abstract:

The wireless sensor networks have been extensively deployed and researched. One of the major issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to prolong the lifetime of a wireless sensor networks. In the paper, we compare several clustering protocols which significantly affect a balancing of energy consumption. And we propose an Energy-Efficient Distributed Unequal Clustering (EEDUC) algorithm which provides a new way of creating distributed clusters. In EEDUC, each sensor node sets the waiting time. This waiting time is considered as a function of residual energy, number of neighborhood nodes. EEDUC uses waiting time to distribute cluster heads. We also propose an unequal clustering mechanism to solve the hot-spot problem. Simulation results show that EEDUC distributes the cluster heads, balances the energy consumption well among the cluster heads and increases the network lifetime.

Keywords: Wireless Sensor Network, Distributed UnequalClustering, Multi-hop, Lifetime.

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2281 A New Source Code Auditing Algorithm for Detecting LFI and RFI in PHP Programs

Authors: Seyed Ali Mir Heydari, Mohsen Sayadiharikandeh

Abstract:

Static analysis of source code is used for auditing web applications to detect the vulnerabilities. In this paper, we propose a new algorithm to analyze the PHP source code for detecting LFI and RFI potential vulnerabilities. In our approach, we first define some patterns for finding some functions which have potential to be abused because of unhandled user inputs. More precisely, we use regular expression as a fast and simple method to define some patterns for detection of vulnerabilities. As inclusion functions could be also used in a safe way, there could occur many false positives (FP). The first cause of these FP-s could be that the function does not use a usersupplied variable as an argument. So, we extract a list of usersupplied variables to be used for detecting vulnerable lines of code. On the other side, as vulnerability could spread among the variables like by multi-level assignment, we also try to extract the hidden usersupplied variables. We use the resulted list to decrease the false positives of our method. Finally, as there exist some ways to prevent the vulnerability of inclusion functions, we define also some patterns to detect them and decrease our false positives.

Keywords: User-supplied Variables, hidden user-supplied variables, PHP vulnerabilities.

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2280 Join and Meet Block Based Default Definite Decision Rule Mining from IDT and an Incremental Algorithm

Authors: Chen Wu, Jingyu Yang

Abstract:

Using maximal consistent blocks of tolerance relation on the universe in incomplete decision table, the concepts of join block and meet block are introduced and studied. Including tolerance class, other blocks such as tolerant kernel and compatible kernel of an object are also discussed at the same time. Upper and lower approximations based on those blocks are also defined. Default definite decision rules acquired from incomplete decision table are proposed in the paper. An incremental algorithm to update default definite decision rules is suggested for effective mining tasks from incomplete decision table into which data is appended. Through an example, we demonstrate how default definite decision rules based on maximal consistent blocks, join blocks and meet blocks are acquired and how optimization is done in support of discernibility matrix and discernibility function in the incomplete decision table.

Keywords: rough set, incomplete decision table, maximalconsistent block, default definite decision rule, join and meet block.

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2279 A Survey: Bandwidth Management in an IP Based Network

Authors: M. Kassim, M. Ismail, K. Jumari, M.I Yusof

Abstract:

this paper presented a survey analysis subjected on network bandwidth management from published papers referred in IEEE Explorer database in three years from 2009 to 2011. Network Bandwidth Management is discussed in today-s issues for computer engineering applications and systems. Detailed comparison is presented between published papers to look further in the IP based network critical research area for network bandwidth management. Important information such as the network focus area, a few modeling in the IP Based Network and filtering or scheduling used in the network applications layer is presented. Many researches on bandwidth management have been done in the broad network area but fewer are done in IP Based network specifically at the applications network layer. A few researches has contributed new scheme or enhanced modeling but still the issue of bandwidth management still arise at the applications network layer. This survey is taken as a basic research towards implementations of network bandwidth management technique, new framework model and scheduling scheme or algorithm in an IP Based network which will focus in a control bandwidth mechanism in prioritizing the network traffic the applications layer.

Keywords: Bandwidth Management (BM), IP Based network, modeling, algorithm, internet traffic, network Management, Quality of Service (QoS).

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2278 Prediction of the Solubility of Benzoic Acid in Supercritical CO2 Using the PC-SAFT EoS

Authors: Hamidreza Bagheri, Alireza Shariati

Abstract:

There are many difficulties in the purification of raw components and products. However, researchers are seeking better ways for purification. One of the recent methods is extraction using supercritical fluids. In this study, the phase equilibria of benzoic acid -supercritical carbon dioxide system were investigated. Regarding the phase equilibria of this system, the modeling of solid-supercritical fluid behavior was performed using the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) and Peng-Robinson equations of state (PR EoS). For this purpose, five PC-SAFT EoS parameters for pure benzoic acid were obtained using its experimental vapor pressure. Benzoic acid has association sites and the behavior of the benzoic acid-supercritical fluid system was well predicted using both equations of state, while the binary interaction parameter values for PR EoS were negative. Genetic algorithm, which is one of the most accurate global optimization algorithms, was also used to optimize the pure benzoic acid parameters and the binary interaction parameters. The AAD% value for the PC-SAFT EoS, were 0.22 for the carbon dioxide-benzoic acid system.

Keywords: Supercritical fluids, Solubility, Solid, PC-SAFT EoS, Genetic algorithm.

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2277 Performance Comparison of Particle Swarm Optimization with Traditional Clustering Algorithms used in Self-Organizing Map

Authors: Anurag Sharma, Christian W. Omlin

Abstract:

Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of an adaptive heuristic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOM. The application of our method to several standard data sets demonstrates its feasibility. PSO algorithm utilizes a so-called U-matrix of SOM to determine cluster boundaries; the results of this novel automatic method compare very favorably to boundary detection through traditional algorithms namely k-means and hierarchical based approach which are normally used to interpret the output of SOM.

Keywords: cluster boundaries, clustering, code vectors, data mining, particle swarm optimization, self-organizing maps, U-matrix.

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2276 Random Projections for Dimensionality Reduction in ICA

Authors: Sabrina Gaito, Andrea Greppi, Giuliano Grossi

Abstract:

In this paper we present a technique to speed up ICA based on the idea of reducing the dimensionality of the data set preserving the quality of the results. In particular we refer to FastICA algorithm which uses the Kurtosis as statistical property to be maximized. By performing a particular Johnson-Lindenstrauss like projection of the data set, we find the minimum dimensionality reduction rate ¤ü, defined as the ratio between the size k of the reduced space and the original one d, which guarantees a narrow confidence interval of such estimator with high confidence level. The derived dimensionality reduction rate depends on a system control parameter β easily computed a priori on the basis of the observations only. Extensive simulations have been done on different sets of real world signals. They show that actually the dimensionality reduction is very high, it preserves the quality of the decomposition and impressively speeds up FastICA. On the other hand, a set of signals, on which the estimated reduction rate is greater than 1, exhibits bad decomposition results if reduced, thus validating the reliability of the parameter β. We are confident that our method will lead to a better approach to real time applications.

Keywords: Independent Component Analysis, FastICA algorithm, Higher-order statistics, Johnson-Lindenstrauss lemma.

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2275 Anti-Aging Effects of Retinol and Alpha Hydroxy Acid on Elastin Fibers of Artificially Photo-Aged Human Dermal Fibroblast Cell Lines

Authors: M. Jarrar, S. Behl, N. Shaheen, A. Fatima, R. Nasab

Abstract:

Skin aging is a slow multifactorial process influenced by both internal as well as external factors. Ultra-violet radiations (UV), diet, smoking and personal habits are the most common environmental factors that affect skin aging. Fat contents and fibrous proteins as collagen and elastin are core internal structural components. The direct influence of UV on elastin integrity and health is central on aging of skin especially by time. The deposition of abnormal elastic material is a major marker in a photo-aged skin. Searching for compounds that may protect against cutaneous photodamage is exceedingly valued. Retinoids and alpha hydroxy acids have been endorsed by some researchers as possible candidates for protecting and or repairing the effect of UV damaged skin. For consolidating a better system of anti- and protective effects of such anti-aging agents, we evaluated the combinatory effects of various dosages of lactic acid and retinol on the dermal fibroblast’s elastin levels exposed to UV. The UV exposed cells showed significant reduction in the elastin levels. A combination of drugs with a higher concentration of lactic acid (30 -35 mM) and a lower concentration of retinol (10-15mg/mL) showed to work better in maintaining elastin concentration in UV exposed cells. We assume this preservation could be the result of increased tropo-elastin gene expression stimulated by retinol whereas lactic acid probably repaired the UV irradiated damage by enhancing the amount and integrity of the elastin fibers.

Keywords: Alpha Hydroxy Acid, Elastin, Retinol, Ultraviolet radiations.

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2274 Environmental Impacts of Point and Non-Point Source Pollution in Krishnagiri Reservoir: A Case Study in South India

Authors: N. K. Ambujam, V. Sudha

Abstract:

Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.

Keywords: Hyper-eutrophication, Krishnagiri reservoir, nutrients, NPS pollution.

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2273 Optimal Allocation of DG Units for Power Loss Reduction and Voltage Profile Improvement of Distribution Networks using PSO Algorithm

Authors: K. Varesi

Abstract:

This paper proposes a Particle Swarm Optimization (PSO) based technique for the optimal allocation of Distributed Generation (DG) units in the power systems. In this paper our aim is to decide optimal number, type, size and location of DG units for voltage profile improvement and power loss reduction in distribution network. Two types of DGs are considered and the distribution load flow is used to calculate exact loss. Load flow algorithm is combined appropriately with PSO till access to acceptable results of this operation. The suggested method is programmed under MATLAB software. Test results indicate that PSO method can obtain better results than the simple heuristic search method on the 30-bus and 33- bus radial distribution systems. It can obtain maximum loss reduction for each of two types of optimally placed multi-DGs. Moreover, voltage profile improvement is achieved.

Keywords: Distributed Generation (DG), Optimal Allocation, Particle Swarm Optimization (PSO), Power Loss Minimization, Voltage Profile Improvement.

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2272 Sinusoidal Roughness Elements in a Square Cavity

Authors: M. Yousaf, S. Usman

Abstract:

Numerical studies were conducted using Lattice Boltzmann Method (LBM) to study the natural convection in a square cavity in the presence of roughness. An algorithm based on a single relaxation time Bhatnagar-Gross-Krook (BGK) model of Lattice Boltzmann Method (LBM) was developed. Roughness was introduced on both the hot and cold walls in the form of sinusoidal roughness elements. The study was conducted for a Newtonian fluid of Prandtl number (Pr) 1.0. The range of Ra number was explored from 10^3 to 10^6 in a laminar region. Thermal and hydrodynamic behavior of fluid was analyzed using a differentially heated square cavity with roughness elements present on both the hot and cold wall. Neumann boundary conditions were introduced on horizontal walls with vertical walls as isothermal. The roughness elements were at the same boundary condition as corresponding walls. Computational algorithm was validated against previous benchmark studies performed with different numerical methods, and a good agreement was found to exist. Results indicate that the maximum reduction in the average heat transfer was 16.66 percent at Ra number 10^5.

Keywords: Lattice Boltzmann Method Natural convection, Nusselt Number Rayleigh number, Roughness.

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2271 Optimal Design of Airfoil Platform Shapes with High Aspect Ratio Using Genetic Algorithm

Authors: Kyoungwoo Park, Byeong-Sam Kim

Abstract:

Unmanned aerial vehicles (UAVs) performing their operations for a long time have been attracting much attention in military and civil aviation industries for the past decade. The applicable field of UAV is changing from the military purpose only to the civil one. Because of their low operation cost, high reliability and the necessity of various application areas, numerous development programs have been initiated around the world. To obtain the optimal solutions of the design variable (i.e., sectional airfoil profile, wing taper ratio and sweep) for high performance of UAVs, both the lift and lift-to-drag ratio are maximized whereas the pitching moment should be minimized, simultaneously. It is found that the lift force and lift-to-drag ratio are linearly dependent and a unique and dominant solution are existed. However, a trade-off phenomenon is observed between the lift-to-drag ratio and pitching moment. As the result of optimization, sixty-five (65) non-dominated Pareto individuals at the cutting edge of design spaces that are decided by airfoil shapes can be obtained.

Keywords: Unmanned aerial vehicle (UAV), Airfoil, CFD, Shape optimization, Genetic Algorithm.

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2270 Image Dehazing Using Dark Channel Prior and Fast Guided Filter in Daubechies Lifting Wavelet Transform Domain

Authors: Harpreet Kaur, Sudipta Majumdar

Abstract:

In this paper a method for image dehazing is proposed in lifting wavelet transform domain. Lifting Daubechies (D4) wavelet has been used to obtain the approximate image and detail images.  As the haze is contained in low frequency part, only the approximate image is used for further processing. This region is processed by dehazing algorithm based on dark channel prior (DCP). The dehazed approximate image is then recombined with the detail images using inverse lifting wavelet transform. Implementation of lifting wavelet transform has the advantage of auxiliary memory saving, fast implementation and simplicity. Also, the proposed method deals with near white scene problem, blue horizon issue and localized light sources in a way to enhance image quality and makes the algorithm robust. Simulation results present improvement in terms of visual quality, parameters such as root mean square (RMS) contrast, structural similarity index (SSIM), entropy and execution time.

Keywords: Dark channel prior, image dehazing, lifting wavelet transform.

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2269 Super Resolution Blind Reconstruction of Low Resolution Images using Wavelets based Fusion

Authors: Liyakathunisa, V. K. Ananthashayana

Abstract:

Crucial information barely visible to the human eye is often embedded in a series of low resolution images taken of the same scene. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. The ideal algorithm should be fast, and should add sharpness and details, both at edges and in regions without adding artifacts. In this paper we propose a super resolution blind reconstruction technique for linearly degraded images. In our proposed technique the algorithm is divided into three parts an image registration, wavelets based fusion and an image restoration. In this paper three low resolution images are considered which may sub pixels shifted, rotated, blurred or noisy, the sub pixel shifted images are registered using affine transformation model; A wavelet based fusion is performed and the noise is removed using soft thresolding. Our proposed technique reduces blocking artifacts and also smoothens the edges and it is also able to restore high frequency details in an image. Our technique is efficient and computationally fast having clear perspective of real time implementation.

Keywords: Affine Transforms, Denoiseing, DWT, Fusion, Image registration.

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2268 Zhou Enlai’s Impact to the Foreign Folicy of China

Authors: Nazira B. Boldurukova

Abstract:

The main aim of this article is to give the information about life and social and diplomatic work of Zhou Enlai, to prove his identity in his impact to the history of the world; to show his place in the organization of internal and foreign policy and in the peaceful international relationships of China with other countries.

Keywords: China, foreign policy of China, identity, politician, diplomacy, Zhou Enlai.

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