Search results for: Automatic background extraction

Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8.

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Authors: Azlin S Azmi, Mus’ab Zainal, Sarina Sulaiman, Azura Amid, Zaki Zainudin

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Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO₃ concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h^-1 at 0% NPK, 2500 lux, 40^oC and 0% NaNO₃. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30^oC and 1% NaNO₃.

Keywords: Cyanobacteria, lipid, mutant, marine Synechococcus sp. PCC 7002, specific growth rate.

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Authors: Chockpisit Thepsithar, Nongnuch Euawong, Nukul Jonghomkajorn

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The in vitro culture procedure of purple nutsedge (Cyperus rotundus L.) for multiple shoot induction and tuber formation was established. Multiple shoots were significantly induced from a single shoot of about 0.5 – 0.8 cm long, on Murashige and Skoog (MS) medium supplemented with 4.44 μM 6- benzyladinine (BA) alone or in combination with 2.85 μM 1- indoleacetic acid (IAA), providing 17.6 and 15.3 shoots per explant with 31.2 and 27.5 leaves per explant, respectively, within 6 weeks of culturing. Moreover, MS medium supplemented with 4.44 μM BA and 2.85 μM IAA was suitable for tuber induction, obtaining 5.9 tubers with 3.4 rhizomes per explant. In combination with ancymidol and higher concentration of sucrose, 11.1 μM BA and 60 g/L sucrose or 11.1 μM BA, 7.8 μM ancymidol and 60 g/L sucrose induced 3.5 tubers with 1.6 rhizomes or 3.5 tubers without rhizome, respectively. However, MS medium containing 3.9 or 7.8 μM ancymidol in combination with either 60 or 80 g/L sucrose enchanced significant root formation at 20.9 – 23.6 roots per explant.

Keywords: Purple nutsedge, Cyperus rotundus, multiple shoot induction, tuber formation

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Authors: St. Karagiannis, A. I. Dounis, T. Chalastras, P. Tiropanis, D. Papachristos

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This work presents the design of an expert system that aims in the procurement of patient medial background and in the search for suitable skin test selections. Skin testing is the tool used most widely to diagnose allergies. The language of expert systems CLIPS is used as a tool of designing. Finally, we present the evaluation of the proposed expert system which was achieved with the import of certain medical cases and the system produced with suitable successful skin tests.

Keywords: Artificial intelligence, expert system - CLIPS, allergy and skin test.

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: Intrusion prevention, network security, optimal policy, Q-learning.

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Authors: Mahmoud A. Rabah

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Preparation of size controlled nano-particles of silver catalyst on carbon substrate from e-waste has been investigated. Chemical route was developed by extraction of the metals available in nitric acid followed by treatment with hydrofluoric acid. Silver metal particles deposited with an average size 4-10 nm. A stabilizer concentration of 10- 40 g/l was used. The average size of the prepared silver decreased with increase of the anode current density. Size uniformity of the silver nano-particles was improved distinctly at higher current density no more than 20mA... Grain size increased with EK time whereby aggregation of particles was observed after 6 h of reaction.. The chemical method involves adsorption of silver nitrate on the carbon substrate. Adsorbed silver ions were directly reduced to metal particles using hydrazine hydrate. Another alternative method is by treatment with ammonia followed by heating the carbon loaded-silver hydroxide at 980°C. The product was characterized with the help of XRD, XRF, ICP, SEM and TEM techniques.

Keywords: e-waste, silver catalyst, metals recovery, electrokinetic process.

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Authors: R. AliMohammadzadeh, M. Haghir Chehreghani, A. Zarnani, M. Rahgozar

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Mining frequent tree patterns have many useful applications in XML mining, bioinformatics, network routing, etc. Most of the frequent subtree mining algorithms (i.e. FREQT, TreeMiner and CMTreeMiner) use anti-monotone property in the phase of candidate subtree generation. However, none of these algorithms have verified the correctness of this property in tree structured data. In this research it is shown that anti-monotonicity does not generally hold, when using weighed support in tree pattern discovery. As a result, tree mining algorithms that are based on this property would probably miss some of the valid frequent subtree patterns in a collection of trees. In this paper, we investigate the correctness of anti-monotone property for the problem of weighted frequent subtree mining. In addition we propose W3-Miner, a new algorithm for full extraction of frequent subtrees. The experimental results confirm that W3-Miner finds some frequent subtrees that the previously proposed algorithms are not able to discover.

Keywords: Semi-Structured Data Mining, Anti-Monotone Property, Trees.

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Authors: Jalil Z., Farooq M., Zafar H., Sabir M., Ashraf E.

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Internet is largely composed of textual contents and a huge volume of digital contents gets floated over the Internet daily. The ease of information sharing and re-production has made it difficult to preserve author-s copyright. Digital watermarking came up as a solution for copyright protection of plain text problem after 1993. In this paper, we propose a zero text watermarking algorithm based on occurrence frequency of non-vowel ASCII characters and words for copyright protection of plain text. The embedding algorithm makes use of frequency non-vowel ASCII characters and words to generate a specialized author key. The extraction algorithm uses this key to extract watermark, hence identify the original copyright owner. Experimental results illustrate the effectiveness of the proposed algorithm on text encountering meaning preserving attacks performed by five independent attackers.

Keywords: Copyright protection, Digital watermarking, Document authentication, Information security, Watermark.

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Authors: Oral Lacin, Turan Calban, Fatih Sevim, Taner Celik

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In this study, Pb²⁺ uptake by the hydroxyapatite nanopowders (n-Hap) from aqueous solutions was investigated by using batch adsorption techniques. The adsorption equilibrium studies were carried out as a function of contact time, adsorbent dosage, pH, temperature, and initial Pb²⁺ concentration. The results showed that the equilibrium time of adsorption was achieved within 60 min, and the effective pH was selected to be 5 (natural pH). The maximum adsorption capacity of Pb²⁺ on n-Hap was found as 565 mg.g^-1. It is believed that the results obtained for adsorption may provide a background for the detailed mechanism investigations and the pilot and industrial scale applications.

Keywords: Nanopowders, hydroxyapatite, heavy metals, adsorption.

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Authors: Muhammad Shafi, Paul W. H. Chung

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This paper proposes a hybrid method for eyes localization in facial images. The novelty is in combining techniques that utilise colour, edge and illumination cues to improve accuracy. The method is based on the observation that eye regions have dark colour, high density of edges and low illumination as compared to other parts of face. The first step in the method is to extract connected regions from facial images using colour, edge density and illumination cues separately. Some of the regions are then removed by applying rules that are based on the general geometry and shape of eyes. The remaining connected regions obtained through these three cues are then combined in a systematic way to enhance the identification of the candidate regions for the eyes. The geometry and shape based rules are then applied again to further remove the false eye regions. The proposed method was tested using images from the PICS facial images database. The proposed method has 93.7% and 87% accuracies for initial blobs extraction and final eye detection respectively.

Keywords: Erosion, dilation, Edge-density

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Authors: Benedetto Manganelli, Beniamino Murgante

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The use of statistical data and of the neural networks, capable of elaborate a series of data and territorial info, have allowed the making of a model useful in the subdivision of urban places into homogeneous zone under the profile of a social, real estate, environmental and urbanist background of a city. The development of homogeneous zone has fiscal and urbanist advantages. The tools in the model proposed, able to be adapted to the dynamic changes of the city, allow the application of the zoning fast and dynamic.

Keywords: Homogeneous Urban Areas, Multidimensional Scaling, Neural Network, Real Estate Market, Urban Planning.

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Authors: Edjere Oghenekohwiroro, Asibor Irabor Godwin, Uwem Bassey

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This paper determines the presence and levels of phthalates in sachet and borehole water source in some parts of Delta State, Nigeria. Sachet and borehole water samples were collected from seven different water packaging facilities and level of phthalates determined using GC-MS instrumentation. Phthalates concentration in borehole samples varied from 0.00-0.01 (DMP), 0.06-0.20 (DEP), 0.10-0.98 (DBP), 0.21-0.36 (BEHP), 0.01-0.03 (DnOP) µg/L and (BBP) was not detectable; while sachet water varied from 0.03-0.95 (DMP), 0.16-12.45 (DEP), 0.57-3.38 (DBP), 0.00-0.03 (BBP), 0.08-0.31 (BEHP) and 0-0.03 (DnOP) µg/L. Phthalates concentration in the sachet water was higher than that of the corresponding boreholes sources and also showed significant difference (p < 0.05) between the two. Sources of these phthalate esters were the interaction between water molecules and plastic storage facilities. Although concentration of all phthalate esters analyzed were lower than the threshold limit value(TLV), over time storage of water samples in this medium can lead to substantial increase with negative effects on individuals consuming them.

Keywords: Phthalate esters, borehole, sachet water, sample extraction, gas chromatography, GC-MS.

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Authors: Yu-Min Chang, Kuo-Sheng Tsai, Hung-Te Tsai, Chia-Hsin Li

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This paper presents the early-warning lights classification management system for industrial parks promoted by the Taiwan Environmental Protection Administration (EPA) since 2011, including the definition of each early-warning light, objectives, action program and accomplishments. All of the 151 industrial parks in Taiwan were classified into four early-warning lights, including red, orange, yellow and green, for carrying out respective pollution management according to the monitoring data of soil and groundwater quality, regulatory compliance, and regulatory listing of control site or remediation site. The Taiwan EPA set up a priority list for high potential polluted industrial parks and investigated their soil and groundwater qualities based on the results of the light classification and pollution potential assessment. In 2011-2013, there were 44 industrial parks selected and carried out different investigation, such as the early warning groundwater well networks establishment and pollution investigation/verification for the red and orange-light industrial parks and the environmental background survey for the yellow-light industrial parks. Among them, 22 industrial parks were newly or continuously confirmed that the concentrations of pollutants exceeded those in soil or groundwater pollution control standards. Thus, the further investigation, groundwater use restriction, listing of pollution control site or remediation site, and pollutant isolation measures were implemented by the local environmental protection and industry competent authorities; the early warning lights of those industrial parks were proposed to adjust up to orange or red-light. Up to the present, the preliminary positive effect of the soil and groundwater quality management system for industrial parks has been noticed in several aspects, such as environmental background information collection, early warning of pollution risk, pollution investigation and control, information integration and application, and inter-agency collaboration. Finally, the work and goal of self-initiated quality management of industrial parks will be carried out on the basis of the inter-agency collaboration by the classified lights system of early warning and management as well as the regular announcement of the status of each industrial park.

Keywords: Industrial park, soil and groundwater quality management, early-warning lights classification, SOP for reporting and treatment of monitored abnormal events.

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Authors: N. B. Mahesh Kumar, K. Premalatha

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The inherent skin patterns created at the joints in the finger exterior are referred as finger knuckle-print. It is exploited to identify a person in a unique manner because the finger knuckle print is greatly affluent in textures. In biometric system, the region of interest is utilized for the feature extraction algorithm. In this paper, local and global features are extracted separately. Fast Discrete Orthonormal Stockwell Transform is exploited to extract the local features. Global feature is attained by escalating the size of Fast Discrete Orthonormal Stockwell Transform to infinity. Two features are fused to increase the recognition accuracy. A matching distance is calculated for both the features individually. Then two distances are merged mutually to acquire the final matching distance. The proposed scheme gives the better performance in terms of equal error rate and correct recognition rate.

Keywords: Hamming distance, Instantaneous phase, Region of Interest, Recognition accuracy.

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Authors: F. Meskine, N. Taleb, M. Chikr El-Mezouar, K. Kpalma, A. Almhdie

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Image registration is the process of establishing point by point correspondence between images obtained from a same scene. This process is very useful in remote sensing, medicine, cartography, computer vision, etc. Then, the task of registration is to place the data into a common reference frame by estimating the transformations between the data sets. In this work, we develop a rigid point registration method based on the application of genetic algorithms and Hausdorff distance. First, we extract the feature points from both images based on the algorithm of global and local curvature corner. After refining the feature points, we use Hausdorff distance as similarity measure between the two data sets and for optimizing the search space we use genetic algorithms to achieve high computation speed for its inertial parallel. The results show the efficiency of this method for registration of satellite images.

Keywords: Feature extraction, Genetic algorithms, Hausdorff distance, Image registration, Point registration.

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Authors: Seyyed Yasser Hashemi, Khalil Monfaredi

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Automatic transformation of paper documents into electronic documents requires document segmentation at the first stage. However, some parameters restrictions such as variations in character font sizes, different text line spacing, and also not uniform document layout structures altogether have made it difficult to design a general-purpose document layout analysis algorithm for many years. Thus in most previously reported methods it is inevitable to include these parameters. This problem becomes excessively acute and severe, especially in Persian/Arabic documents. Since the Persian/Arabic scripts differ considerably from the English scripts, most of the proposed methods for the English scripts do not render good results for the Persian scripts. In this paper, we present a novel parameter-free method for segmenting the Persian/Arabic document images which also works well for English scripts. This method segments the document image into maximal homogeneous regions and identifies them as texts and non-texts based on a pyramidal image structure. In other words the proposed method is capable of document segmentation without considering the character font sizes, text line spacing, and document layout structures. This algorithm is examined for 150 Arabic/Persian and English documents and document segmentation process are done successfully for 96 percent of documents.

Keywords: Persian/Arabic document, document segmentation, Pyramidal Image Structure, skew detection and correction.

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Authors: N. Moghadam, H. Sadeghi

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In this paper a novel scheme for watermarking digital audio during its compression to MPEG-1 Layer III format is proposed. For this purpose we slightly modify some of the selected MDCT coefficients, which are used during MPEG audio compression procedure. Due to the possibility of modifying different MDCT coefficients, there will be different choices for embedding the watermark into audio data, considering robustness and transparency factors. Our proposed method uses a genetic algorithm to select the best coefficients to embed the watermark. This genetic selection is done according to the parameters that are extracted from the perceptual content of the audio to optimize the robustness and transparency of the watermark. On the other hand the watermark security is increased due to the random nature of the genetic selection. The information of the selected MDCT coefficients that carry the watermark bits, are saves in a database for future extraction of the watermark. The proposed method is suitable for online MP3 stores to pursue illegal copies of musical artworks. Experimental results show that the detection ratio of the watermarks at the bitrate of 128kbps remains above 90% while the inaudibility of the watermark is preserved.

Keywords: Content-Based Audio Watermarking, Genetic AudioWatermarking.

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Authors: Revaz Chigladze

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The purpose of the research is to investigate the surfaces of Jupiter's Galilean moons (satellites), namely to identify which moon has the most uniform surface among them, what is the difference between the front (in the direction of motion) and the back sides of each moon's surface, as well as the temporal variations of the moons. Since 1981, the E. Kharadze Georgian National Astrophysical Observatory has been conducting polarimetric (P) and photometric (M) observations of Jupiter's Galilean moons with telescopes of different diameters (40-cm and 125-cm), as well as polarimeter Automatic Scanning Electron Polarimeter (ASEP)-78, the latest generation photometer with polarimeter and modern light receiver Santana Barbara Instrument Group (SBIG). As it turns out from the analysis of the observed material, parameters P and M depend on: α, the phase angle of the moon (satellite); L, the orbital latitude of the moon (satellite); λ, the wavelength, and t, the period of observation, i.e., P = P (α, L, λ, t), and similarly: M = M (α, L, λ, t). Based on the analysis of the obtained results, we get: The magnitude of the degree of polarization of Jupiter's Galilean moons near the opposition significantly differs from zero. Europa appears to have the most uniform surface, and Callisto has the least. Time variations are most characteristic of Io, which confirms the presence of volcanic activity on its surface. Based on the observed materials, it can be seen that the intensity of light reflected from the front hemisphere of the first three moons: Io, Europa, and Ganymede, is less than the intensity of light reflected from the rear hemisphere, while the picture with Callisto is opposite. The paper provides an explanation of this fact.

Keywords: Galilean moons, polarization, degree of polarization, photometry, front and rear hemispheres.

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and electrocardiogram (ECG)-based systems are unquestionably the best choice due to their appealing inherent characteristics. The Convolutional Neural Networks (CNNs) are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the caliber of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest False Acceptance Rate (FAR)  of 0.04% and the highest False Rejection Rate (FRR)  of 5%, the best performing network achieved an identification accuracy of 99.94%. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable, but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, dense networks, identification rate, train/test split ratio.

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Authors: Justin Leo Cheang Loong, Khazaimatol S Subari, Muhammad Kamil Abdullah, Nurul Nadia Ahmad, RosliBesar

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Heart sound is an acoustic signal and many techniques used nowadays for human recognition tasks borrow speech recognition techniques. One popular choice for feature extraction of accoustic signals is the Mel Frequency Cepstral Coefficients (MFCC) which maps the signal onto a non-linear Mel-Scale that mimics the human hearing. However the Mel-Scale is almost linear in the frequency region of heart sounds and thus should produce similar results with the standard cepstral coefficients (CC). In this paper, MFCC is investigated to see if it produces superior results for PCG based human identification system compared to CC. Results show that the MFCC system is still superior to CC despite linear filter-banks in the lower frequency range, giving up to 95% correct recognition rate for MFCC and 90% for CC. Further experiments show that the high recognition rate is due to the implementation of filter-banks and not from Mel-Scaling.

Keywords: Biometric, Phonocardiogram, Cepstral Coefficients, Mel Frequency

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Authors: M. Mohamadi, A. M. Maskooki., S. A. Mortazavi

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The quality and shelf life of foods of containing lipids (fats and oils) significantly reduces due to rancidity.Applications of natural antioxidants are one of the most effective manners to prevent the oxidation of oils and lipids. The antioxidant properties of juice extracted from barberry fruit (Berberris vulgaris.L) using maceration and SWE (10 bars and 120 - 180°C) methods were investigated and compared with conventional method. The amount of phenolic compound and reduction power of all samples were determined and the data were statistically analyzed using multifactor design. The results showed that the total amount of phenolic compound increased with increasing of pressure and temprature from 1861.9 to 2439.1 (mg Gallic acid /100gr Dry matter). The ability of reduction power of SWE obtained antioxidant extract compared with BHA (synthetic antioxidant) and ascorbic acid (natural antioxidant). There were significant differences among reduction power of extracts and there were remarkable difference with BHA and Ascorbic acid (P<0.01).

Keywords: Subcritical water, Antioxidant, Barberry, Phenolic compound, Reduction power

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Authors: Nemir Al-Azzawi, Harsa A. Mat Sakim, Wan Ahmed K. Wan Abdullah, Yasmin Mohd Yacob

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Feature-based registration is an effective technique for clinical use, because it can greatly reduce computational costs. However, this technique, which estimates the transformation by using feature points extracted from two images, may cause misalignments. To handle with this limitation, we propose to extract the salient edges and extracted control points (CP) of medical images by using efficiency of multiresolution representation of data nonsubsampled contourlet transform (NSCT) that finds the best feature points. The MR images were first decomposed using the NSCT, and then Edge and CP were extracted from bandpass directional subband of NSCT coefficients and some proposed rules. After edge and CP extraction, mutual information was adopted for the registration of feature points and translation parameters are calculated by using particle swarm optimization (PSO). The experimental results showed that the proposed method produces totally accurate performance for registration medical CT-MR images.

Keywords: Feature-based registration, mutual information, nonsubsampled contourlet transform, particle swarm optimization.

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Authors: Banaja Mohanty, Prakash Kumar Hota

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This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.

Keywords: Automatic generation control, governor dead band, generation rate constraint, differential evolution.

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Authors: Wei Zhang, Xin Zhao, Yi-Fan Zhu, Xin-Jian Zhang

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Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.

Keywords: admissible support vector kernel, reproducing kernel, reproducing kernel Hilbert space, Green function, support vectorregression

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Authors: Anju Shri, Parvinder S. Sandhu, Vikas Gupta, Sanyam Anand

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In literature, there are metrics for identifying the quality of reusable components but the framework that makes use of these metrics to precisely predict reusability of software components is still need to be worked out. These reusability metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the software component and hence improve the productivity due to probabilistic increase in the reuse level. As CK metric suit is most widely used metrics for extraction of structural features of an object oriented (OO) software; So, in this study, tuned CK metric suit i.e. WMC, DIT, NOC, CBO and LCOM, is used to obtain the structural analysis of OO-based software components. An algorithm has been proposed in which the inputs can be given to K-Means Clustering system in form of tuned values of the OO software component and decision tree is formed for the 10-fold cross validation of data to evaluate the in terms of linguistic reusability value of the component. The developed reusability model has produced high precision results as desired.

Keywords: CK-Metric, Desicion Tree, Kmeans, Reusability.

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Authors: S. Chahba, R. Sehab, A. Akrad, C. Morel

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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: Electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit fault diagnosis, artificial neural network.

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Authors: Matías Micheletto, Rodrigo Santos, Sergio F. Ochoa

Abstract:

In developing countries, most roads in rural areas are dirt road. They require frequent maintenance since they are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the maintenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: Dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision.

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Authors: Commander Sunil Tyagi

Abstract:

Effectiveness of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) classifiers for fault diagnosis of rolling element bearings are presented in this paper. The characteristic features of vibration signals of rotating driveline that was run in its normal condition and with faults introduced were used as input to ANN and SVM classifiers. Simple statistical features such as standard deviation, skewness, kurtosis etc. of the time-domain vibration signal segments along with peaks of the signal and peak of power spectral density (PSD) are used as features to input the ANN and SVM classifier. The effect of preprocessing of the vibration signal by Discreet Wavelet Transform (DWT) prior to feature extraction is also studied. It is shown from the experimental results that the performance of SVM classifier in identification of bearing condition is better then ANN and pre-processing of vibration signal by DWT enhances the effectiveness of both ANN and SVM classifier

Keywords: ANN, Artificial Intelligence, Fault Diagnosis, Pattern Recognition, Rolling Element Bearing, SVM. Wavelet Transform

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Authors: Hamimah Adnan, Norfashiha Hashim, Mohd Arif Marhani, Mohd Asri Yeop Johari

Abstract:

The aim of this paper is to provide a better understanding of the implementation of Project Management practices by UiTM contractors to ensure project success. A questionnaire survey was administered to 120 UiTM contractors in Malaysia. The purpose of this method was to gather information on the contractors- project background and project management skills. It was found that all of the contractors had basic knowledge and understanding of project management skills. It is suggested that a reasonable project plan and an appropriate organizational structure are influential factors for project success. It is recommended that the contractors need to have an effective program of work and up to date information system are emphasized.

Keywords: Project management, success, contractors.

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Authors: Hanan Moawad, Naglaa M. Abd EL-Rahman

Abstract:

Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.

Keywords: Ultrasound, classical extract, Biological control, Erwinia carotovora, Hyphaene thebaica.

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