Search results for: Control Approach.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8110

Search results for: Control Approach.

5560 On the Need to have an Additional Methodology for the Psychological Product Measurement and Evaluation

Authors: Corneliu Sofronie, Roxana Zubcov

Abstract:

Cognitive Science appeared about 40 years ago, subsequent to the challenge of the Artificial Intelligence, as common territory for several scientific disciplines such as: IT, mathematics, psychology, neurology, philosophy, sociology, and linguistics. The new born science was justified by the complexity of the problems related to the human knowledge on one hand, and on the other by the fact that none of the above mentioned sciences could explain alone the mental phenomena. Based on the data supplied by the experimental sciences such as psychology or neurology, models of the human mind operation are built in the cognition science. These models are implemented in computer programs and/or electronic circuits (specific to the artificial intelligence) – cognitive systems – whose competences and performances are compared to the human ones, leading to the psychology and neurology data reinterpretation, respectively to the construction of new models. During these processes if psychology provides the experimental basis, philosophy and mathematics provides the abstraction level utterly necessary for the intermission of the mentioned sciences. The ongoing general problematic of the cognitive approach provides two important types of approach: the computational one, starting from the idea that the mental phenomenon can be reduced to 1 and 0 type calculus operations, and the connection one that considers the thinking products as being a result of the interaction between all the composing (included) systems. In the field of psychology measurements in the computational register use classical inquiries and psychometrical tests, generally based on calculus methods. Deeming things from both sides that are representing the cognitive science, we can notice a gap in psychological product measurement possibilities, regarded from the connectionist perspective, that requires the unitary understanding of the quality – quantity whole. In such approach measurement by calculus proves to be inefficient. Our researches, deployed for longer than 20 years, lead to the conclusion that measuring by forms properly fits to the connectionism laws and principles.

Keywords: complementary methodology, connection approach, networks without scaling, quantum psychology.

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5559 Brain MRI Segmentation and Lesions Detection by EM Algorithm

Authors: Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane

Abstract:

In Multiple Sclerosis, pathological changes in the brain results in deviations in signal intensity on Magnetic Resonance Images (MRI). Quantitative analysis of these changes and their correlation with clinical finding provides important information for diagnosis. This constitutes the objective of our work. A new approach is developed. After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation. Our approach is based on building statistical model from data itself, for normal brain MRI and including clustering tissue type. Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model. We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.

Keywords: EM algorithm, Magnetic Resonance Imaging, Mathematical morphology, Markov random model.

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5558 Sensor and Actuator Fault Detection in Connected Vehicles under a Packet Dropping Network

Authors: Z. Abdollahi Biron, P. Pisu

Abstract:

Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Keywords: Fault diagnostics, communication network, connected vehicles, packet drop out, platoon.

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5557 Evaluation of Anti-Varroa Bottom Boards to Control Small Hive Beetle (Aethina tumida)

Authors: M. Keshlaf, R. Spooner-Hart

Abstract:

Australia does not have varroa mite. However, we investigated the efficacy of modified hive bottom boards used for varroa mite management in honeybee colonies to control small hive beetle, Aethina tumida. We assessed infestation levels between hives fitted with tube, mesh and conventional (solid) bottom boards in Richmond, NSW eastern Australian. Colonies housed in hives with tube bottom boards were significantly superior to those in hives with conventional and mesh bottom boards. Even though in-hive beetle populations were generally low during the trial period, hives fitted with tube bottom boards however, had fewer small hive beetles than other hives. Although the trial was conducted over only one season, it suggests that there may be benefit in Australian beekeepers changing from using conventional bottom boards even with the absence of varroa mite, when small hive beetle is present.

Keywords: Aethina tumida, Apis mellifera, mesh bottom boards, tube bottom boards.

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5556 Real Time Remote Monitoring and Fault Detection in Wind Turbine

Authors: Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui

Abstract:

In new energy development, wind power has boomed. It is due to the proliferation of wind parks and their operation in supplying the national electric grid with low cost and clean resources. Hence, there is an increased need to establish a proactive maintenance for wind turbine machines based on remote control and monitoring. That is necessary with a real-time wireless connection in offshore or inaccessible locations while the wired method has many flaws. The objective of this strategy is to prolong wind turbine lifetime and to increase productivity. The hardware of a remote control and monitoring system for wind turbine parks is designed. It takes advantage of GPRS or Wi-Max wireless module to collect data measurements from different wind machine sensors through IP based multi-hop communication. Computer simulations with Proteus ISIS and OPNET software tools have been conducted to evaluate the performance of the studied system. Study findings show that the designed device is suitable for application in a wind park.

Keywords: Embedded System, Monitoring, Wind Turbine, Faults Diagnosis, TCP/IP Protocol, Real Time, Web.

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5555 A Methodological Approach for Detecting Burst Noise in the Time Domain

Authors: Liu Dan, Wang Xue, Wang Guiqin, Qian Zhihong

Abstract:

The burst noise is a kind of noises that are destructive and frequently found in semiconductor devices and ICs, yet detecting and removing the noise has proved challenging for IC designers or users. According to the properties of burst noise, a methodological approach is presented (proposed) in the paper, by which the burst noise can be analysed and detected in time domain. In this paper, principles and properties of burst noise are expounded first, Afterwards, feasibility (viable) of burst noise detection by means of wavelet transform in the time domain is corroborated in the paper, and the multi-resolution characters of Gaussian noise, burst noise and blurred burst noise are discussed in details by computer emulation. Furthermore, the practical method to decide parameters of wavelet transform is acquired through a great deal of experiment and data statistics. The methodology may yield an expectation in a wide variety of applications.

Keywords: Burst noise, detection, wavelet transform

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5554 Quantitative Study for Exchange of Gases from Open Sewer Channel to Atmosphere

Authors: Asif Mansoor, Nasiruddin Khan, Noreen Jamil

Abstract:

In this communication a quantitative modeling approach is applied to construct model for the exchange of gases from open sewer channel to the atmosphere. The data for the exchange of gases of the open sewer channel for the year January 1979 to December 2006 is utilized for the construction of the model. The study reveals that stream flow of the open sewer channel exchanges the toxic gases continuously with time varying scale. We find that the quantitative modeling approach is more parsimonious model for these exchanges. The usual diagnostic tests are applied for the model adequacy. This model is beneficial for planner and managerial bodies for the improvement of implemented policies to overcome future environmental problems.

Keywords: Open sewer channel, Industrial waste, Municipalwaste, Gases exchange, Atmosphere, Stochastic models, Diagnosticschecks.

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5553 A Text Classification Approach Based on Natural Language Processing and Machine Learning Techniques

Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

Abstract:

Automatic text classification applies mostly natural language processing (NLP) and other artificial intelligence (AI)-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: Machine learning, text classification, NLP techniques, semantic representation.

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5552 Optimization of Flexible Job Shop Scheduling Problem with Sequence Dependent Setup Times Using Genetic Algorithm Approach

Authors: Sanjay Kumar Parjapati, Ajai Jain

Abstract:

This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: Flexible Job Shop, Genetic Algorithm, Makespan, Sequence Dependent Setup Times.

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5551 Physical and Mechanical Performance of Mortars with Ashes from Straw and Bagasse Sugarcane

Authors: Débora C. G. Oliveira, Julio D. Salles, Bruna A. Moriy, João A. Rossignolo, Holmer Savastano JR.

Abstract:

The objective of this study was to identify the optimal level of partial replacement of Portland cement by the ashes originating from burning straw and bagasse from sugar cane (ASB). Order to this end, were made five series of flat plates and cylindrical bodies: control and others with the partial replacement in 20, 30, 40 and 50% of ASB in relation to the mass of the Ordinary Portland cement, and conducted a mechanical testing of simple axial compression (cylindrical bodies) and the four-point bending (flat plates) and determined water absorption (WA), bulk density (BD) and apparent void volume (AVV) on both types of specimens. Based on the data obtained, it may be noted that the control treatment containing only Portland cement, obtained the best results. However, the cylindrical bodies with 20% ashes showed better results compared to the other treatments. And in the formulations plates, the treatment which showed the best results was 30% cement replacement by ashes.

Keywords: Modulus of rupture, simple axial compression, waste.

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5550 The Potential Effect of Biochar Application on Microbial Activities and Availability of Mineral Nitrogen in Arable Soil Stressed by Drought

Authors: Helena Dvořáčková, Jakub Elbl, Irina Mikajlo, Antonín Kintl, Jaroslav Hynšt, Olga Urbánková, Jaroslav Záhora

Abstract:

Application of biochar to arable soils represents a new approach to restore soil health and quality. Many studies reported the positive effect of biochar application on soil fertility and development of soil microbial community. Moreover biochar may affect the soil water retention, but this effect has not been sufficiently described yet. Therefore this study deals with the influence of biochar application on: microbial activities in soil, availability of mineral nitrogen in soil for microorganisms, mineral nitrogen retention and plant production. To demonstrate the effect of biochar addition on the above parameters, the pot experiment was realized. As a model crop, Lactuca sativa L. was used and cultivated from December 10th 2014 till March 22th 2015 in climate chamber in thoroughly homogenized arable soil with and without addition of biochar. Five variants of experiment (V1 – V5) with different regime of irrigation were prepared. Variants V1 – V2 were fertilized by mineral nitrogen, V3 – V4 by biochar and V5 was a control. The significant differences were found only in plant production and mineral nitrogen retention. The highest content of mineral nitrogen in soil was detected in V1 and V2, about 250 % in comparison with the other variants. The positive effect of biochar application on soil fertility, mineral nitrogen availability was not found. On the other hand results of plant production indicate the possible positive effect of biochar application on soil water retention.

Keywords: Arable soil, biochar, drought, mineral Nitrogen.

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5549 Biokinetics of Coping Mechanism of Freshwater tilapia following Exposure to Waterborne and Dietary Copper

Authors: Jeng-Wei Tsai

Abstract:

The purpose of this study was to understand the main sources of copper (Cu) accumulation in target organs of tilapia (Oreochromis mossambicus) and to investigate how the organism mediate the process of Cu accumulation under prolonged conditions. By measuring both dietary and waterborne Cu accumulation and total concentrations in tilapia with biokinetic modeling approach, we were able to clarify the biokinetic coping mechanisms for the long term Cu accumulation. This study showed that water and food are both the major source of Cu for the muscle and liver of tilapia. This implied that control the Cu concentration in these two routes will be correlated to the Cu bioavailability for tilapia. We found that exposure duration and level of waterborne Cu drove the Cu accumulation in tilapia. The ability for Cu biouptake and depuration in organs of tilapia were actively mediated under prolonged exposure conditions. Generally, the uptake rate, depuration rate and net bioaccumulation ability in all selected organs decreased with the increasing level of waterborne Cu and extension of exposure duration.Muscle tissues accounted for over 50%of the total accumulated Cu and played a key role in buffering the Cu burden in the initial period of exposure, alternatively, the liver acted a more important role in the storage of Cu with the extension of exposures. We concluded that assumption of the constant biokinetic rates could lead to incorrect predictions with overestimating the long-term Cu accumulation in ecotoxicological risk assessments.

Keywords: Biokinetics, Chronic exposure, Copper, Coping mechanism, Tilapia

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5548 Environmental Management in Arid Regions:The Question of Water

Authors: Yousef Bakhbakhi, Mourad Boumaza

Abstract:

Only recently have water ethics received focused interest in the international water community. Because water is metabolically basic to life, an ethical dimension persists in every decision related to water. Water ethics at once express human society-s approach to water and act as guidelines for behaviour. Ideas around water are often implicit and embedded as assumptions. They can be entrenched in behaviour and difficult to contest because they are difficult to “see". By explicitly revealing the ethical ideas underlying water-related decisions, human society-s relationship with water, and with natural systems of which water is part, can be contested and shifted or be accepted with conscious intention by human society. In recent decades, improved understanding of water-s importance for ecosystem functioning and ecological services for human survival is moving us beyond this growth-driven, supplyfocused management paradigm. Environmental ethics challenge this paradigm by extending the ethical sphere to the environment and thus water or water Resources management per se. An ethical approach is a legitimate, important, and often ignored approach to effect change in environmental decision making. This qualitative research explores principles of water ethics and examines the underlying ethical precepts of selected water policy examples. The constructed water ethic principles act as a set of criteria against which a policy comparison can be established. This study shows that water Resources management is a progressive issue by embracing full public participation and a new planning model, and knowledgegeneration initiatives.

Keywords: water resources, environmental management, publicparticipation.

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5547 An Optimal Steganalysis Based Approach for Embedding Information in Image Cover Media with Security

Authors: Ahlem Fatnassi, Hamza Gharsellaoui, Sadok Bouamama

Abstract:

This paper deals with the study of interest in the fields of Steganography and Steganalysis. Steganography involves hiding information in a cover media to obtain the stego media in such a way that the cover media is perceived not to have any embedded message for its unintended recipients. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can lead to the prevention of disastrous security incidents. In this paper, we provide a critical review of the steganalysis algorithms available to analyze the characteristics of an image stego media against the corresponding cover media and understand the process of embedding the information and its detection. We anticipate that this paper can also give a clear picture of the current trends in steganography so that we can develop and improvise appropriate steganalysis algorithms.

Keywords: Optimization, heuristics and metaheuristics algorithms, embedded systems, low-power consumption, Steganalysis Heuristic approach.

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5546 Deep-Learning Based Approach to Facial Emotion Recognition Through Convolutional Neural Network

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

Abstract:

Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning.

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5545 Knowledge Management Criteria among Malaysian Organizations: An ANOVA Approach

Authors: Reza Sigari Tabrizi, Yeap Peik Foong, Nazli Ebrahimi

Abstract:

The Knowledge Management (KM) Criteria is an essential foundation to evaluate KM outcomes. Different sets of criteria were developed and tailored by many researchers to determine the results of KM initiatives. However, literature review has emphasized on incomplete set of criteria for evaluating KM outcomes. Hence, this paper tried to address the problem of determining the criteria for measuring knowledge management outcomes among different types of Malaysian organizations. Successively, this paper was assumed to develop widely accepted criteria to measure success of knowledge management efforts for Malaysian organizations. Our analysis approach was based on the ANOVA procedure to compare a set of criteria among different types of organizations. This set of criteria was exploited from literature review. It is hoped that this study provides a better picture for different types of Malaysian organizations to establish a comprehensive set of criteria due to measure results of KM programs.

Keywords: KM Criteria, Knowledge Management, KMOutcomes, ANOVA

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5544 Automatic Generation of OWL Ontologies from UML Class Diagrams Based on Meta- Modelling and Graph Grammars

Authors: Aissam Belghiat, Mustapha Bourahla

Abstract:

Models are placed by modeling paradigm at the center of development process. These models are represented by languages, like UML the language standardized by the OMG which became necessary for development. Moreover the ontology engineering paradigm places ontologies at the center of development process; in this paradigm we find OWL the principal language for knowledge representation. Building ontologies from scratch is generally a difficult task. The bridging between UML and OWL appeared on several regards such as the classes and associations. In this paper, we have to profit from convergence between UML and OWL to propose an approach based on Meta-Modelling and Graph Grammars and registered in the MDA architecture for the automatic generation of OWL ontologies from UML class diagrams. The transformation is based on transformation rules; the level of abstraction in these rules is close to the application in order to have usable ontologies. We illustrate this approach by an example.

Keywords: ATOM3, MDA, Ontology, OWL, UML

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5543 Effect of Concrete Nonlinear Parameters on the Seismic Response of Concrete Gravity Dams

Authors: Z. Heirany, M. Ghaemian

Abstract:

Behavior of dams against the seismic loads has been studied by many researchers. Most of them proposed new numerical methods to investigate the dam safety. In this paper, to study the effect of nonlinear parameters of concrete in gravity dams, a twodimensional approach was used including the finite element method, staggered method and smeared crack approach. Effective parameters in the models are physical properties of concrete such as modulus of elasticity, tensile strength and specific fracture energy. Two different models were used in foundation (mass-less and massed) in order to determine the seismic response of concrete gravity dams. Results show that when the nonlinear analysis includes the dam- foundation interaction, the foundation-s mass, flexibility and radiation damping are important in gravity dam-s response.

Keywords: Numerical methods; concrete gravity dams; finiteelement method; boundary condition

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5542 A Linearization and Decomposition Based Approach to Minimize the Non-Productive Time in Transfer Lines

Authors: Hany Osman, M. F. Baki

Abstract:

We address the balancing problem of transfer lines in this paper to find the optimal line balancing that minimizes the nonproductive time. We focus on the tool change time and face orientation change time both of which influence the makespane. We consider machine capacity limitations and technological constraints associated with the manufacturing process of auto cylinder heads. The problem is represented by a mixed integer programming model that aims at distributing the design features to workstations and sequencing the machining processes at a minimum non-productive time. The proposed model is solved by an algorithm established using linearization schemes and Benders- decomposition approach. The experiments show the efficiency of the algorithm in reaching the exact solution of small and medium problem instances at reasonable time.

Keywords: Transfer line balancing, Benders' decomposition, Linearization.

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5541 Panoramic Sensor Based Blind Spot Accident Prevention System

Authors: Rajendra Prasad Mahapatra, K. Vimal Kumar

Abstract:

There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..

Keywords: Panoramic sensors, Blind spot, Convex lens, Computer Vision, Sonar.

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5540 Neural Network Based Approach for Face Detection cum Face Recognition

Authors: Kesari Verma, Aniruddha S. Thoke, Pritam Singh

Abstract:

Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.

Keywords: Face Detection, Face Recognition, NN Approach, PCA Algorithm.

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5539 A Survey on Quasi-Likelihood Estimation Approaches for Longitudinal Set-ups

Authors: Naushad Mamode Khan

Abstract:

The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood-based estimating methodology. The joint generalized quasi-likelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill-conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQL-III) that is based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: Longitudinal, Com-Poisson, Ill-conditioned, INAR(1), GLMS, GQL.

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5538 Aircraft Selection Using Multiple Criteria Decision Making Analysis Method with Different Data Normalization Techniques

Authors: C. Ardil

Abstract:

This paper presents an original application of multiple criteria decision making analysis theory to the evaluation of aircraft selection problem. The selection of an optimal, efficient and reliable fleet, network and operations planning policy is one of the most important factors in aircraft selection problem. Given that decision making in aircraft selection involves the consideration of a number of opposite criteria and possible solutions, such a selection can be considered as a multiple criteria decision making analysis problem. This study presents a new integrated approach to decision making by considering the multiple criteria utility theory and the maximal regret minimization theory methods as well as aircraft technical, economical, and environmental aspects. Multiple criteria decision making analysis method uses different normalization techniques to allow criteria to be aggregated with qualitative and quantitative data of the decision problem. Therefore, selecting a suitable normalization technique for the model is also a challenge to provide data aggregation for the aircraft selection problem. To compare the impact of different normalization techniques on the decision problem, the vector, linear (sum), linear (max), and linear (max-min) data normalization techniques were identified to evaluate aircraft selection problem. As a logical implication of the proposed approach, it enhances the decision making process through enabling the decision maker to: (i) use higher level knowledge regarding the selection of criteria weights and the proposed technique, (ii) estimate the ranking of an alternative, under different data normalization techniques and integrated criteria weights after a posteriori analysis of the final rankings of alternatives. A set of commercial passenger aircraft were considered in order to illustrate the proposed approach. The obtained results of the proposed approach were compared using Spearman's rho tests. An analysis of the final rank stability with respect to the changes in criteria weights was also performed so as to assess the sensitivity of the alternative rankings obtained by the application of different data normalization techniques and the proposed approach.

Keywords: Normalization Techniques, Aircraft Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, MCDMA

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5537 Retrospective Reconstruction of Time Series Data for Integrated Waste Management

Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

Abstract:

The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modeling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modeling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modeling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: Content analysis, factors, integrated waste management system, time series.

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5536 Data Acquisition from Cell Phone using Logical Approach

Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung, Jae-Cheol Ryou

Abstract:

Cell phone forensics to acquire and analyze data in the cellular phone is nowadays being used in a national investigation organization and a private company. In order to collect cellular phone flash memory data, we have two methods. Firstly, it is a logical method which acquires files and directories from the file system of the cell phone flash memory. Secondly, we can get all data from bit-by-bit copy of entire physical memory using a low level access method. In this paper, we describe a forensic tool to acquire cell phone flash memory data using a logical level approach. By our tool, we can get EFS file system and peek memory data with an arbitrary region from Korea CDMA cell phone.

Keywords: Forensics, logical method, acquisition, cell phone, flash memory.

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5535 A VR Cybersecurity Training Knowledge-Based Ontology

Authors: Shaila Rana, Wasim Alhamdani

Abstract:

Effective cybersecurity learning relies on an engaging, interactive, and entertaining activity that fosters positive learning outcomes. VR cybersecurity training may provide a training format that is engaging, interactive, and entertaining. A methodological approach and framework are needed to allow trainers and educators to employ VR cybersecurity training methods to promote positive learning outcomes. Thus, this paper aims to create an approach that cybersecurity trainers can follow to create a VR cybersecurity training module. This methodology utilizes concepts from other cybersecurity training frameworks, such as NICE and CyTrONE. Other cybersecurity training frameworks do not incorporate the use of VR. VR training proposes unique challenges that cannot be addressed in current cybersecurity training frameworks. Subsequently, this ontology utilizes concepts to develop VR training to create a relevant methodology for creating VR cybersecurity training modules.

Keywords: Virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training, ontology.

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5534 Liver Tumor Detection by Classification through FD Enhancement of CT Image

Authors: N. Ghatwary, A. Ahmed, H. Jalab

Abstract:

In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: Fractional differential (FD), Computed Tomography (CT), fusion.

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5533 Color Image Enhancement Using Multiscale Retinex and Image Fusion Techniques

Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

Abstract:

In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: Image Enhancement, Multiscale Retinex, Image Fusion.

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5532 Alignment of MG-63 Osteoblasts on Fibronectin-Coated Phosphorous Doping Lattices in Silicon

Authors: Andreas Körtge, Susanne Stählke, Regina Lange, Mario Birkholz, Mirko Fraschke, Katrin Schulz, Barbara Nebe, Patrick Elter

Abstract:

A major challenge in biomaterials research is the regulation of protein adsorption which is a key factor for controlling the subsequent cell adhesion at implant surfaces. The aim of the present study was to control the adsorption of fibronectin (FN) and the attachment of MG-63 osteoblasts with an electronic nanostructure. Shallow doping line lattices with a period of 260 nm were produced for this purpose by implantation of phosphorous in silicon wafers. Protein coverage was determined after incubating the substrate with FN by means of an immunostaining procedure and the measurement of the fluorescence intensity with a TECAN analyzer. We observed an increased amount of adsorbed FN on the nanostructure compared to control substrates. MG-63 osteoblasts were cultivated for 24h on FN-incubated substrates and their morphology was assessed by SEM. Preferred orientation and elongation of the cells in direction of the doping lattice lines was observed on FN-coated nanostructures.

Keywords: Cell adhesion, electronic nanostructures, doping lattice, fibronectin, MG-63 osteoblasts, protein adsorption.

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5531 Identifying Unknown Dynamic Forces Applied on Two Dimensional Frames

Authors: H. Katkhuda

Abstract:

A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: Dynamic Force Identification, Dynamic Responses, Sub-structure and Time Domain.

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