Search results for: Extraction and data integration
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8495

Search results for: Extraction and data integration

6935 A Keyword-Based Filtering Technique of Document-Centric XML using NFA Representation

Authors: Changwoo Byun, Kyounghan Lee, Seog Park

Abstract:

XML is becoming a de facto standard for online data exchange. Existing XML filtering techniques based on a publish/subscribe model are focused on the highly structured data marked up with XML tags. These techniques are efficient in filtering the documents of data-centric XML but are not effective in filtering the element contents of the document-centric XML. In this paper, we propose an extended XPath specification which includes a special matching character '%' used in the LIKE operation of SQL in order to solve the difficulty of writing some queries to adequately filter element contents using the previous XPath specification. We also present a novel technique for filtering a collection of document-centric XMLs, called Pfilter, which is able to exploit the extended XPath specification. We show several performance studies, efficiency and scalability using the multi-query processing time (MQPT).

Keywords: XML Data Stream, Document-centric XML, Filtering Technique, Value-based Predicates.

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6934 A Mixture Model of Two Different Distributions Approach to the Analysis of Heterogeneous Survival Data

Authors: Ülkü Erişoğlu, Murat Erişoğlu, Hamza Erol

Abstract:

In this paper we propose a mixture of two different distributions such as Exponential-Gamma, Exponential-Weibull and Gamma-Weibull to model heterogeneous survival data. Various properties of the proposed mixture of two different distributions are discussed. Maximum likelihood estimations of the parameters are obtained by using the EM algorithm. Illustrative example based on real data are also given.

Keywords: Exponential-Gamma, Exponential-Weibull, Gamma-Weibull, EM Algorithm, Survival Analysis.

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6933 Recovering Artifacts from Legacy Systems Using Pattern Matching

Authors: Ghulam Rasool, Ilka Philippow

Abstract:

Modernizing legacy applications is the key issue facing IT managers today because there's enormous pressure on organizations to change the way they run their business to meet the new requirements. The importance of software maintenance and reengineering is forever increasing. Understanding the architecture of existing legacy applications is the most critical issue for maintenance and reengineering. The artifacts recovery can be facilitated with different recovery approaches, methods and tools. The existing methods provide static and dynamic set of techniques for extracting architectural information, but are not suitable for all users in different domains. This paper presents a simple and lightweight pattern extraction technique to extract different artifacts from legacy systems using regular expression pattern specifications with multiple language support. We used our custom-built tool DRT to recover artifacts from existing system at different levels of abstractions. In order to evaluate our approach a case study is conducted.

Keywords: Artifacts recovery, Pattern matching, Reverseengineering, Program understanding, Regular expressions, Sourcecode analysis.

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6932 Design and Optimization of Coplanar Waveguide-Fed Sensing Antennas for ISM Band Applications

Authors: Vivek Bharti, Inderpreet Kaur, Saurabh Verma, Renu Gangwar, Hari Kumar Singh

Abstract:

This work presents a dual-band Coplanar Waveguide (CPW) fed rectangular patch antenna designed for applications in Industrial, Scientific, and Medical (ISM) Band sensing. Fabricated on a cost-effective FR-4 substrate with specific dimensions, the antenna incorporates a rectangular slot and a copper patch, optimized through simulation to achieve desired characteristics, particularly focusing on the reflection coefficient. A unique feature is introduced through the integration of copper cells forming a Partially Reflecting Surface (PRS) to feed the antenna. Dual-band functionality is achieved, covering frequencies of 1.28 GHz-1.3 GHz and 4.9 GHz-5.2 GHz, catering to diverse communication needs within these frequency ranges. The addition of a superstrate enhances the antenna’s gain, resulting in 4.5 dBi at 1.28 GHz-1.3 GHz and 6.5 dBi at 4.9 GHz-5.2 GHz, with an efficiency of 58%.

Keywords: ISM, Coplanar waveguide fed, superstrate, circularly polarized.

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6931 DCBOR: A Density Clustering Based on Outlier Removal

Authors: A. M. Fahim, G. Saake, A. M. Salem, F. A. Torkey, M. A. Ramadan

Abstract:

Data clustering is an important data exploration technique with many applications in data mining. We present an enhanced version of the well known single link clustering algorithm. We will refer to this algorithm as DCBOR. The proposed algorithm alleviates the chain effect by removing the outliers from the given dataset. So this algorithm provides outlier detection and data clustering simultaneously. This algorithm does not need to update the distance matrix, since the algorithm depends on merging the most k-nearest objects in one step and the cluster continues grow as long as possible under specified condition. So the algorithm consists of two phases; at the first phase, it removes the outliers from the input dataset. At the second phase, it performs the clustering process. This algorithm discovers clusters of different shapes, sizes, densities and requires only one input parameter; this parameter represents a threshold for outlier points. The value of the input parameter is ranging from 0 to 1. The algorithm supports the user in determining an appropriate value for it. We have tested this algorithm on different datasets contain outlier and connecting clusters by chain of density points, and the algorithm discovers the correct clusters. The results of our experiments demonstrate the effectiveness and the efficiency of DCBOR.

Keywords: Data Clustering, Clustering Algorithms, Handling Noise, Arbitrary Shape of Clusters.

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6930 Alternative to M-Estimates in Multisensor Data Fusion

Authors: Nga-Viet Nguyen, Georgy Shevlyakov, Vladimir Shin

Abstract:

To solve the problem of multisensor data fusion under non-Gaussian channel noise. The advanced M-estimates are known to be robust solution while trading off some accuracy. In order to improve the estimation accuracy while still maintaining the equivalent robustness, a two-stage robust fusion algorithm is proposed using preliminary rejection of outliers then an optimal linear fusion. The numerical experiments show that the proposed algorithm is equivalent to the M-estimates in the case of uncorrelated local estimates and significantly outperforms the M-estimates when local estimates are correlated.

Keywords: Data fusion, estimation, robustness, M-estimates.

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6929 Data Structures and Algorithms of Intelligent Web-Based System for Modular Design

Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.

Keywords: Data structures, algorithms, intelligent web-based system, modular design.

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6928 Sprayer Boom Active Suspension Using Intelligent Active Force Control

Authors: M. Tahmasebi, R.A. Rahman, M. Mailah, M. Gohari

Abstract:

The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.

Keywords: Active force control, sprayer boom, active suspension, iterative learning.

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6927 Self Watermarking based on Visual Cryptography

Authors: Mahmoud A. Hassan, Mohammed A. Khalili

Abstract:

We are proposing a simple watermarking method based on visual cryptography. The method is based on selection of specific pixels from the original image instead of random selection of pixels as per Hwang [1] paper. Verification information is generated which will be used to verify the ownership of the image without the need to embed the watermark pattern into the original digital data. Experimental results show the proposed method can recover the watermark pattern from the marked data even if some changes are made to the original digital data.

Keywords: Watermarking, visual cryptography, visualthreshold.

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6926 On the Dynamic Model of Service Innovation in Manufacturing Industry

Authors: Yongyoon Suh, Chulhyun Kim, Moon-soo Kim

Abstract:

As the trend of manufacturing is being dominated depending on services, products and processes are more and more related with sophisticated services. Thus, this research starts with the discussion about integration of the product, process, and service in the innovation process. In particular, this paper sets out some foundations for a theory of service innovation in the field of manufacturing, and proposes the dynamic model of service innovation related to product and process. Two dynamic models of service innovation are suggested to investigate major tendencies and dynamic variations during the innovation cycle: co-innovation and sequential innovation. To structure dynamic models of product, process, and service innovation, the innovation stages in which two models are mainly achieved are identified. The research would encourage manufacturers to formulate strategy and planning for service development with product and process.

Keywords: dynamic model, service innovation, service innovation models, innovation cycle, manufacturing industry.

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6925 A New Framework to Model a Secure E-Commerce System

Authors: A. Youseef, F. Liu

Abstract:

The existing information system (IS) developments methods are not met the requirements to resolve the security related IS problems and they fail to provide a successful integration of security and systems engineering during all development process stages. Hence, the security should be considered during the whole software development process and identified with the requirements specification. This paper aims to propose an integrated security and IS engineering approach in all software development process stages by using i* language. This proposed framework categorizes into three separate parts: modelling business environment part, modelling information technology system part and modelling IS security part. The results show that considering security IS goals in the whole system development process can have a positive influence on system implementation and better meet business expectations.

Keywords: Business Process Modelling (BPM), Information System Security, Software Development Process, Requirement Engineering.

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6924 Estimation of Missing or Incomplete Data in Road Performance Measurement Systems

Authors: Kristjan Kuhi, Kati K. Kaare, Ott Koppel

Abstract:

Modern management in most fields is performance based; both planning and implementation of maintenance and operational activities are driven by appropriately defined performance indicators. Continuous real-time data collection for management is becoming feasible due to technological advancements. Outdated and insufficient input data may result in incorrect decisions. When using deterministic models the uncertainty of the object state is not visible thus applying the deterministic models are more likely to give false diagnosis. Constructing structured probabilistic models of the performance indicators taking into consideration the surrounding indicator environment enables to estimate the trustworthiness of the indicator values. It also assists to fill gaps in data to improve the quality of the performance analysis and management decisions. In this paper authors discuss the application of probabilistic graphical models in the road performance measurement and propose a high-level conceptual model that enables analyzing and predicting more precisely future pavement deterioration based on road utilization.

Keywords: Probabilistic graphical models, performance indicators, road performance management, data collection

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6923 Frame Texture Classification Method (FTCM) Applied on Mammograms for Detection of Abnormalities

Authors: Kjersti Engan, Karl Skretting, Jostein Herredsvela, Thor Ole Gulsrud

Abstract:

Texture classification is an important image processing task with a broad application range. Many different techniques for texture classification have been explored. Using sparse approximation as a feature extraction method for texture classification is a relatively new approach, and Skretting et al. recently presented the Frame Texture Classification Method (FTCM), showing very good results on classical texture images. As an extension of that work the FTCM is here tested on a real world application as detection of abnormalities in mammograms. Some extensions to the original FTCM that are useful in some applications are implemented; two different smoothing techniques and a vector augmentation technique. Both detection of microcalcifications (as a primary detection technique and as a last stage of a detection scheme), and soft tissue lesions in mammograms are explored. All the results are interesting, and especially the results using FTCM on regions of interest as the last stage in a detection scheme for microcalcifications are promising.

Keywords: detection, mammogram, texture classification, dictionary learning, FTCM

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6922 Detailed Mapping of Pyroclastic Flow Deposits by SAR Data Processing for an Active Volcano in the Torrid Zone

Authors: Asep Saepuloh, Katsuaki Koike

Abstract:

Field mapping activity for an active volcano mainly in the Torrid Zone is usually hampered by several problems such as steep terrain and bad atmosphere conditions. In this paper we present a simple solution for such problem by a combination Synthetic Aperture Radar (SAR) and geostatistical methods. By this combination, we could reduce the speckle effect from the SAR data and then estimate roughness distribution of the pyroclastic flow deposits. The main purpose of this study is to detect spatial distribution of new pyroclastic flow deposits termed as P-zone accurately using the β°data from two RADARSAT-1 SAR level-0 data. Single scene of Hyperion data and field observation were used for cross-validation of the SAR results. Mt. Merapi in central Java, Indonesia, was chosen as a study site and the eruptions in May-June 2006 were examined. The P-zones were found in the western and southern flanks. The area size and the longest flow distance were calculated as 2.3 km2 and 6.8 km, respectively. The grain size variation of the P-zone was mapped in detail from fine to coarse deposits regarding the C-band wavelength of 5.6 cm.

Keywords: Geostatistical Method, Mt. Merapi, Pyroclastic, RADARSAT-1.

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6921 Power System Load Shedding: Key Issues and New Perspectives

Authors: H. Bevrani, A. G. Tikdari, T. Hiyama

Abstract:

Optimal load shedding (LS) design as an emergency plan is one of the main control challenges posed by emerging new uncertainties and numerous distributed generators including renewable energy sources in a modern power system. This paper presents an overview of the key issues and new challenges on optimal LS synthesis concerning the integration of wind turbine units into the power systems. Following a brief survey on the existing LS methods, the impact of power fluctuation produced by wind powers on system frequency and voltage performance is presented. The most LS schemas proposed so far used voltage or frequency parameter via under-frequency or under-voltage LS schemes. Here, the necessity of considering both voltage and frequency indices to achieve a more effective and comprehensive LS strategy is emphasized. Then it is clarified that this problem will be more dominated in the presence of wind turbines.

Keywords: Load shedding, emergency control, voltage, frequency, wind turbine.

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6920 TOSOM: A Topic-Oriented Self-Organizing Map for Text Organization

Authors: Hsin-Chang Yang, Chung-Hong Lee, Kuo-Lung Ke

Abstract:

The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method.

Keywords: Self-organizing map, topic identification, learning algorithm, text clustering.

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6919 A Non-Parametric Based Mapping Algorithm for Use in Audio Fingerprinting

Authors: Analise Borg, Paul Micallef

Abstract:

Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organise the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that nonparametric analysis offer potential results as the ones mentioned in the literature.

Keywords: Audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7.

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6918 An Analytical Solution for Vibration of Elevator Cables with Small Bending Stiffness

Authors: R. Mirabdollah Yani, E. Darabi

Abstract:

Responses of the dynamical systems are highly affected by the natural frequencies and it has a huge impact on design and operation of high-rise and high-speed elevators. In the present paper, the variational iteration method (VIM) is employed to investigate better understanding the dynamics of elevator cable as a single-degree-of-freedom (SDOF) swing system. Comparisons made among the results of the proposed closed-form analytical solution, the traditional numerical iterative time integration solution, and the linearized governing equations confirm the accuracy and efficiency of the proposed approach. Furthermore, based on the results of the proposed closed-form solution, the linearization errors in calculating the natural frequencies in different cases are discussed.

Keywords: variational iteration method (VIM), cable vibration, closed-form solution

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6917 Foundation of the Information Model for Connected-Cars

Authors: Hae-Won Seo, Yong-Gu Lee

Abstract:

Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: Connected-car, data modeling, route planning, navigation system.

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6916 Nonlinear Time-History Analysis of 3-Dimensional Semi-rigid Steel Frames

Authors: Phu-Cuong Nguyen, Seung-Eock Kim

Abstract:

This paper presents nonlinear elastic dynamic analysis of 3-D semi-rigid steel frames including geometric and connection nonlinearities. The geometric nonlinearity is considered by using stability functions and updating geometric stiffness matrix. The nonlinear behavior of the steel beam-to-column connection is considered by using a zero-length independent connection element comprising of six translational and rotational springs. The nonlinear dynamic equilibrium equations are solved by the Newmark numerical integration method. The nonlinear time-history analysis results are compared with those of previous studies and commercial SAP2000 software to verify the accuracy and efficiency of the proposed procedure.

Keywords: Geometric nonlinearity, nonlinear time-historyanalysis, semi-rigid connection, stability functions.

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6915 Fault Detection and Identification of COSMED K4b2 Based On PCA and Neural Network

Authors: Jing Zhou, Steven Su, Aihuang Guo

Abstract:

COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.

Keywords: BP Neural Network, Exercising Testing, Fault Detection and Identification, Principal Component Analysis.

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6914 Array Data Transformation for Source Code Obfuscation

Authors: S. Praveen, P. Sojan Lal

Abstract:

Obfuscation is a low cost software protection methodology to avoid reverse engineering and re engineering of applications. Source code obfuscation aims in obscuring the source code to hide the functionality of the codes. This paper proposes an Array data transformation in order to obfuscate the source code which uses arrays. The applications using the proposed data structures force the programmer to obscure the logic manually. It makes the developed obscured codes hard to reverse engineer and also protects the functionality of the codes.

Keywords: Reverse Engineering, Source Code Obfuscation.

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6913 Applying Fuzzy FP-Growth to Mine Fuzzy Association Rules

Authors: Chien-Hua Wang, Wei-Hsuan Lee, Chin-Tzong Pang

Abstract:

In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

Keywords: Data mining, association rule, fuzzy frequent patterngrowth.

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6912 Pulse Oximeter Concept for Vascular Occlusion Test

Authors: Fatanah M. Suhaimi, J. Geoffrey Chase, Christopher G. Pretty, Rodney Elliott, Geoffrey M. Shaw

Abstract:

Microcirculatory dysfunction is very common in sepsis and may results in organ failure and increased risk of death. Analyzing oxygen utilization can potentially assess microcirculation function of an individual. In this study, a modified pulse oximeter is used to extract information signals due to absorption of red (R) and infrared (IR) light. IR and R signal are related to the overall blood volume and reduced hemoglobin, respectively. Differences between these two signals thus represent the amount of oxygenated hemoglobin. Avascular occlusion test has been conducted on healthy individuals to validate the pulse oximeter concept. In this test, both R and IR signals rapidly changed according to the occlusion process. The pulse oximeter concept presented is capable of extracting valuable information to assess microcirculation condition. Implementing this concept on ICU patients has the potential to aid sepsis diagnosis and provide more accurate tracking of patient state and sepsis status.

Keywords: Microcirculation, sepsis, sepsis diagnosis, oxygen extraction.

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6911 Antimicrobial Potentials of Flavonoids Isolated from Tagetes erecta

Authors: N. Behidj-Benyounes, S. Bennaamane, F. Zohra Bissaad, N. Chebouti, H. Mohandkaci, N. Abdalaziz, S. Iddou

Abstract:

In this study, we are interested in a species of the family of Asteraceae (Tagetes erecta). This family is considered as a source of antimicrobial extracts with strong capacity. The extraction of the flavonoids is carried out by the method of liquid/liquid with the use of successive solvents. Afterwards, we evaluated the biological activity of the flavonoids on five pathogenic bacterial stocks such as Escherichia coli, Bacillus subtilis, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus and two stocks of yeasts to knowing Candida albicans) and Saccharomyces cerevisiae, by employing the method of the aromatogramme starting from a solid disc. The result of the antimicrobial activity shows an action and a variable degree of sensitivity according to bacterial stocks tested. It will be noted that the flavonoids have an inhibiting effect on E. coli, B. subtilis, K. pneumoniae and S. aureus. But a resistance with respect to the extract by P. aeruginosa, C. albicans and S. cerevisiae is to be mentioned.

Keywords: Antimicrobial activity, flavonoids, microbial strains, Tagetes erecta L.

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6910 Phytoremediation of Cd and Pb by Four Tropical Timber Species Grown on an Ex-tin Mine in Peninsular Malaysia

Authors: Lai Hoe Ang, Lai Kuen Tang, Wai Mun Ho, Ting Fui Hui, Gary W. Theseira

Abstract:

Contamination of heavy metals in tin tailings has caused an interest in the scientific approach of their remediation. One of the approaches is through phytoremediation, which is using tree species to extract the heavy metals from the contaminated soils. Tin tailings comprise of slime and sand tailings. This paper reports only on the finding of the four timber species namely Acacia mangium, Hopea odorata, Intsia palembanica and Swietenia macrophylla on the removal of cadmium (Cd) and lead (Pb) from the slime tailings. The methods employed for sampling and soil analysis are established methods. Six trees of each species were randomly selected from a 0.25 ha plot for extraction and determination of their heavy metals. The soil samples were systematically collected according to 5 x 5 m grid from each plot. Results showed that the concentration of heavy metals in soils and trees varied according to species. Higher concentration of heavy metals was found in the stem than the primary roots of all the species. A. Mangium accumulated the highest total amount of Pb per hectare basis.

Keywords: Cd, Pb, Phytoremediation of slimetailings, timber species.

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6909 Investigating Crime Hotspot Places and their Implication to Urban Environmental Design: A Geographic Visualization and Data Mining Approach

Authors: Donna R. Tabangin, Jacqueline C. Flores, Nelson F. Emperador

Abstract:

Information is power. Geographical information is an emerging science that is advancing the development of knowledge to further help in the understanding of the relationship of “place" with other disciplines such as crime. The researchers used crime data for the years 2004 to 2007 from the Baguio City Police Office to determine the incidence and actual locations of crime hotspots. Combined qualitative and quantitative research methodology was employed through extensive fieldwork and observation, geographic visualization with Geographic Information Systems (GIS) and Global Positioning Systems (GPS), and data mining. The paper discusses emerging geographic visualization and data mining tools and methodologies that can be used to generate baseline data for environmental initiatives such as urban renewal and rejuvenation. The study was able to demonstrate that crime hotspots can be computed and were seen to be occurring to some select places in the Central Business District (CBD) of Baguio City. It was observed that some characteristics of the hotspot places- physical design and milieu may play an important role in creating opportunities for crime. A list of these environmental attributes was generated. This derived information may be used to guide the design or redesign of the urban environment of the City to be able to reduce crime and at the same time improve it physically.

Keywords: Crime mapping, data mining, environmental design, geographic visualization, GIS.

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6908 Design and Analysis of an Electro Thermally Symmetrical Actuated Microgripper

Authors: Sh. Foroughi, V. Karamzadeh, M. Packirisamy

Abstract:

This paper presents design and analysis of an electrothermally symmetrical actuated microgripper applicable for performing micro assembly or biological cell manipulation. Integration of micro-optics with microdevice leads to achieve extremely precise control over the operation of the device. Geometry, material, actuation, control, accuracy in measurement and temperature distribution are important factors which have to be taken into account for designing the efficient microgripper device. In this work, analyses of four different geometries are performed by means of COMSOL Multiphysics 5.2 with implementing Finite Element Methods. Then, temperature distribution along the fingertip, displacement of gripper site as well as optical efficiency vs. displacement and electrical potential are illustrated. Results show in addition to the industrial application of this device, the usage of that as a cell manipulator is possible.

Keywords: Electro thermal actuator, MEMS, Microgripper, MOEMS.

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6907 An Integrated Framework for the Realtime Investigation of State Space Exploration

Authors: Jörg Lassig, Stefanie Thiem

Abstract:

The objective of this paper is the introduction to a unified optimization framework for research and education. The OPTILIB framework implements different general purpose algorithms for combinatorial optimization and minimum search on standard continuous test functions. The preferences of this library are the straightforward integration of new optimization algorithms and problems as well as the visualization of the optimization process of different methods exploring the search space exclusively or for the real time visualization of different methods in parallel. Further the usage of several implemented methods is presented on the basis of two use cases, where the focus is especially on the algorithm visualization. First it is demonstrated how different methods can be compared conveniently using OPTILIB on the example of different iterative improvement schemes for the TRAVELING SALESMAN PROBLEM. A second study emphasizes how the framework can be used to find global minima in the continuous domain.

Keywords: Global Optimization Heuristics, Particle Swarm Optimization, Ensemble Based Threshold Accepting, Ruin and Recreate

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6906 Learning and Evaluating Possibilistic Decision Trees using Information Affinity

Authors: Ilyes Jenhani, Salem Benferhat, Zied Elouedi

Abstract:

This paper investigates the issue of building decision trees from data with imprecise class values where imprecision is encoded in the form of possibility distributions. The Information Affinity similarity measure is introduced into the well-known gain ratio criterion in order to assess the homogeneity of a set of possibility distributions representing instances-s classes belonging to a given training partition. For the experimental study, we proposed an information affinity based performance criterion which we have used in order to show the performance of the approach on well-known benchmarks.

Keywords: Data mining from uncertain data, Decision Trees, Possibility Theory.

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