Search results for: Testing techniques
601 Trade Openness and Its Effects on Economic Growth in Selected South Asian Countries: A Panel Data Study
Authors: Samra Bajwa, Muhammad W. Siddiqi
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The study investigates the causal link between trade openness and economic growth for four South Asian countries for period 1972-1985 and 1986-2007 to examine the scenario before and after the implementation of SAARC. Panel cointegration and FMOLS techniques are employed for short run and long run estimates. In 1972-85 short run unidirectional causality from GDP to openness is found whereas, in 1986-2007 there exists bi-directional causality between GDP and openness. The long run elasticity magnitude between GDP and openness contains negative sign in 1972-85 which shows that there exists long run negative relationship. While in time period 1986-2007 the elasticity magnitude has positive sign that indicates positive causation between GDP and openness. So it can be concluded that after the implementation of SAARC overall situation of selected countries got better. Also long run coefficient of error term suggests that short term equilibrium adjustments are driven by adjustment back to long run equilibrium.Keywords: Causality, Economic Growth, Panel Co-integration, SAARC, Trade Openness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2636600 Experimental Film Class: Watbangkapom School, Samut Songkhram
Authors: Areerut J.
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Experimental Film Class Project is supported by the Institute for Research and Development at Suan Sunandha Rajabhat University. This project is purported to provide academic and professional services to improve the quality standards of the community and locals in accordance with the mission of the university, which is to improve and expand knowledge for the community and to develop and transfer such knowledge and professions to the next generation. Eventually, it leads to sustainable development because the development of human resources is deemed as the key for sustainable development. Moreover, the Experimental Film Class is an integral part of the teaching of film production at Suan Sunandha International School of Art (SISA). By means of giving opportunities to students for participation in projects by sharing experience, skill and knowledge and participation in field activities, it helps students in the film production major to enhance their abilities and potentials as preparation for their readiness in the marketplace. Additionally, in this class, we provide basic film knowledge, screenwriting techniques, editing and subtitles including uploading videos on social media such as YouTube and Facebook for the participant students.
Keywords: Experimental Film Class, Watbangkapom School, Participant students, Basic of film production, Film Workshop.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2012599 Pattern Recognition Techniques Applied to Biomedical Patterns
Authors: Giovanni Luca Masala
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Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
Keywords: Computer Aided Detection, mammary tumor, pattern recognition, dissimilarity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2348598 Seed-Based Region Growing (SBRG) vs Adaptive Network-Based Inference System (ANFIS) vs Fuzzyc-Means (FCM): Brain Abnormalities Segmentation
Authors: Shafaf Ibrahim, Noor Elaiza Abdul Khalid, Mazani Manaf
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Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.
Keywords: Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS), Fuzzy c-Means (FCM), Brain segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2296597 An Efficient Burst Errors Combating for Image Transmission over Mobile WPANs
Authors: Mohsen A. M. El-Bendary, Mostafa A. R. El-Tokhy
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This paper presents an efficient burst error spreading tool. Also, it studies a vital issue in wireless communications, which is the transmission of images over wireless networks. IEEE ZigBee 802.15.4 is a short-range communication standard that could be used for small distance multimedia transmissions. In fact, the ZigBee network is a Wireless Personal Area Network (WPAN), which needs a strong interleaving mechanism for protection against error bursts. Also, it is low power technology and utilized in the Wireless Sensor Networks (WSN) implementation. This paper presents the chaotic interleaving scheme as a data randomization tool for this purpose. This scheme depends on the chaotic Baker map. The mobility effects on the image transmission are studied with different velocity through utilizing the Jakes’ model. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for image transmission over a correlated fading channel is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes.
Keywords: WPANs, Burst Errors, Mobility, Interleaving Techniques, Fading channels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2024596 Performance of Neural Networks vs. Radial Basis Functions When Forming a Metamodel for Residential Buildings
Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies
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Average temperatures worldwide are expected to continue to rise. At the same time, major cities in developing countries are becoming increasingly populated and polluted. Governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of a model, which is able to estimate the occupant exposure to extreme temperatures and high air pollution within domestic buildings. Building physics simulations were performed using the EnergyPlus building physics software. An accurate metamodel is then formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) have been compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.Keywords: Neural Networks, Radial Basis Functions, Metamodelling, Python machine learning libraries.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2098595 A Hybrid Feature Selection by Resampling, Chi squared and Consistency Evaluation Techniques
Authors: Amir-Massoud Bidgoli, Mehdi Naseri Parsa
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In this paper a combined feature selection method is proposed which takes advantages of sample domain filtering, resampling and feature subset evaluation methods to reduce dimensions of huge datasets and select reliable features. This method utilizes both feature space and sample domain to improve the process of feature selection and uses a combination of Chi squared with Consistency attribute evaluation methods to seek reliable features. This method consists of two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure to find the optimal feature space by applying Chi squared, Consistency subset evaluation methods and genetic search. Experiments on various sized datasets from UCI Repository of Machine Learning databases show that the performance of five classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) improves simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods.Keywords: feature selection, resampling, reliable features, Consistency Subset Evaluation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2576594 Exploration of Autistic Children using Case Based Reasoning System with Cognitive Map
Authors: Ebtehal Alawi Alsaggaf, Shehab A. Gamalel-Din
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Exploring an autistic child in Elementary school is a difficult task that must be fully thought out and the teachers should be aware of the many challenges they face raising their child especially the behavioral problems of autistic children. Hence there arises a need for developing Artificial intelligence (AI) Contemporary Techniques to help diagnosis to discover autistic people. In this research, we suggest designing architecture of expert system that combine Cognitive Maps (CM) with Case Based Reasoning technique (CBR) in order to reduce time and costs of traditional diagnosis process for the early detection to discover autistic children. The teacher is supposed to enter child's information for analyzing by CM module. Then, the reasoning processor would translate the output into a case to be solved a current problem by CBR module. We will implement a prototype for the model as a proof of concept using java and MYSQL. This will be provided a new hybrid approach that will achieve new synergies and improve problem solving capabilities in AI. And we will predict that will reduce time, costs, the number of human errors and make expertise available to more people who want who want to serve autistic children and their families.Keywords: Autism, Cognitive Maps (CM), Case Based Reasoning technique (CBR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1952593 Support Vector Machine based Intelligent Watermark Decoding for Anticipated Attack
Authors: Syed Fahad Tahir, Asifullah Khan, Abdul Majid, Anwar M. Mirza
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In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.Keywords: Bit Correct Ratio (BCR), Grid Search, Intelligent Decoding, Jackknife Technique, Support Vector Machine (SVM), Watermarking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1660592 Fe3O4 and Fe3O4@Au Nanoparticles: Synthesis and Functionalisation for Biomolecular Attachment
Authors: Hendriëtte van der Walt, Lesley Chown, Richard Harris, Ndabenhle Sosibo, Robert Tshikhudo
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The use of magnetic and magnetic/gold core/shell nanoparticles in biotechnology or medicine has shown good promise due to their hybrid nature which possesses superior magnetic and optical properties. Some of these potential applications include hyperthermia treatment, bio-separations, diagnostics, drug delivery and toxin removal. Synthesis refinement to control geometric and magnetic/optical properties, and finding functional surfactants for biomolecular attachment, are requirements to meet application specifics. Various high-temperature preparative methods were used for the synthesis of iron oxide and gold-coated iron oxide nanoparticles. Different surface functionalities, such as 11-aminoundecanoic and 11-mercaptoundecanoic acid, were introduced on the surface of the particles to facilitate further attachment of biomolecular functionality and drug-like molecules. Nanoparticle thermal stability, composition, state of aggregation, size and morphology were investigated and the results from techniques such as Fourier Transform-Infra Red spectroscopy (FT-IR), Ultraviolet visible spectroscopy (UV-vis), Transmission Electron Microscopy (TEM) and thermal analysis are discussed.Keywords: Core/shell, Iron oxide, Gold coating, Nanoparticles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2937591 Anticancer Effect of Doxorubicin Loaded Heparin based Super-paramagnetic Iron oxide Nanoparticles against the Human Ovarian Cancer Cells
Authors: Amaneh Javid, Shahin Ahmadian, Ali A. Saboury, Saeed Rezaei-Zarchi
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This study determines the effect of naked and heparinbased super-paramagnetic iron oxide nanoparticles on the human cancer cell lines of A2780. Doxorubicin was used as the anticancer drug, entrapped in the SPIO-NPs. This study aimed to decorate nanoparticles with heparin, a molecular ligand for 'active' targeting of cancerous cells and the application of modified-nanoparticles in cancer treatment. The nanoparticles containing the anticancer drug DOX were prepared by a solvent evaporation and emulsification cross-linking method. The physicochemical properties of the nanoparticles were characterized by various techniques, and uniform nanoparticles with an average particle size of 110±15 nm with high encapsulation efficiencies (EE) were obtained. Additionally, a sustained release of DOX from the SPIO-NPs was successful. Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell toxicity than the individual HP and confocal microscopy analysis confirmed excellent cellular uptake efficiency. These results indicate that HP based SPIO-NPs have potential uses as anticancer drug carriers and also have an enhanced anticancer effect.Keywords: Heparin, A2780 cells, ovarian cancer, nanoparticles, doxorubicin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2451590 Social Semantic Web-Based Analytics Approach to Support Lifelong Learning
Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem
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The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.
Keywords: Connectivism, data visualization, informal learning, learning analytics, semantic web, social web.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 798589 A Review and Comparative Analysis on Cluster Ensemble Methods
Authors: S. Sarumathi, P. Ranjetha, C. Saraswathy, M. Vaishnavi, S. Geetha
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Clustering is an unsupervised learning technique for aggregating data objects into meaningful classes so that intra cluster similarity is maximized and inter cluster similarity is minimized in data mining. However, no single clustering algorithm proves to be the most effective in producing the best result. As a result, a new challenging technique known as the cluster ensemble approach has blossomed in order to determine the solution to this problem. For the cluster analysis issue, this new technique is a successful approach. The cluster ensemble's main goal is to combine similar clustering solutions in a way that achieves the precision while also improving the quality of individual data clustering. Because of the massive and rapid creation of new approaches in the field of data mining, the ongoing interest in inventing novel algorithms necessitates a thorough examination of current techniques and future innovation. This paper presents a comparative analysis of various cluster ensemble approaches, including their methodologies, formal working process, and standard accuracy and error rates. As a result, the society of clustering practitioners will benefit from this exploratory and clear research, which will aid in determining the most appropriate solution to the problem at hand.
Keywords: Clustering, cluster ensemble methods, consensus function, data mining, unsupervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 801588 Field Trial of Resin-Based Composite Materials for the Treatment of Surface Collapses Associated with Former Shallow Coal Mining
Authors: Philip T. Broughton, Mark P. Bettney, Isla L. Smail
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Effective treatment of ground instability is essential when managing the impacts associated with historic mining. A field trial was undertaken by the Coal Authority to investigate the geotechnical performance and potential use of composite materials comprising resin and fill or stone to safely treat surface collapses, such as crown-holes, associated with shallow mining. Test pits were loosely filled with various granular fill materials. The fill material was injected with commercially available silicate and polyurethane resin foam products. In situ and laboratory testing was undertaken to assess the geotechnical properties of the resultant composite materials. The test pits were subsequently excavated to assess resin permeation. Drilling and resin injection was easiest through clean limestone fill materials. Recycled building waste fill material proved difficult to inject with resin; this material is thus considered unsuitable for use in resin composites. Incomplete resin permeation in several of the test pits created irregular ‘blocks’ of composite. Injected resin foams significantly improve the stiffness and resistance (strength) of the un-compacted fill material. The stiffness of the treated fill material appears to be a function of the stone particle size, its associated compaction characteristics (under loose tipping) and the proportion of resin foam matrix. The type of fill material is more critical than the type of resin to the geotechnical properties of the composite materials. Resin composites can effectively support typical design imposed loads. Compared to other traditional treatment options, such as cement grouting, the use of resin composites is potentially less disruptive, particularly for sites with limited access, and thus likely to achieve significant reinstatement cost savings. The use of resin composites is considered a suitable option for the future treatment of shallow mining collapses.
Keywords: Composite material, ground improvement, mining legacy, resin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1526587 Enhancing the Effectiveness of Air Defense Systems through Simulation Analysis
Authors: F. Felipe
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Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.Keywords: Air defense, effectiveness, system, simulation, decision-support.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 393586 Fuzzy C-Means Clustering for Biomedical Documents Using Ontology Based Indexing and Semantic Annotation
Authors: S. Logeswari, K. Premalatha
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Search is the most obvious application of information retrieval. The variety of widely obtainable biomedical data is enormous and is expanding fast. This expansion makes the existing techniques are not enough to extract the most interesting patterns from the collection as per the user requirement. Recent researches are concentrating more on semantic based searching than the traditional term based searches. Algorithms for semantic searches are implemented based on the relations exist between the words of the documents. Ontologies are used as domain knowledge for identifying the semantic relations as well as to structure the data for effective information retrieval. Annotation of data with concepts of ontology is one of the wide-ranging practices for clustering the documents. In this paper, indexing based on concept and annotation are proposed for clustering the biomedical documents. Fuzzy c-means (FCM) clustering algorithm is used to cluster the documents. The performances of the proposed methods are analyzed with traditional term based clustering for PubMed articles in five different diseases communities. The experimental results show that the proposed methods outperform the term based fuzzy clustering.
Keywords: MeSH Ontology, Concept Indexing, Annotation, semantic relations, Fuzzy c-means.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2294585 A New Approach to Face Recognition Using Dual Dimension Reduction
Authors: M. Almas Anjum, M. Younus Javed, A. Basit
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In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.Keywords: Biometrics, DCT, Face Recognition, Illumination, Computation, Feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1676584 Survey of Access Controls in Cloud Computing
Authors: Monirah Alkathiry, Hanan Aljarwan
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Cloud computing is one of the most significant technologies that the world deals with, in different sectors with different purposes and capabilities. The cloud faces various challenges in securing data from unauthorized access or modification. Consequently, security risks and levels have greatly increased. Therefore, cloud service providers (CSPs) and users need secure mechanisms that ensure that data are kept secret and safe from any disclosures or exploits. For this reason, CSPs need a number of techniques and technologies to manage and secure access to the cloud services to achieve security goals, such as confidentiality, integrity, identity access management (IAM), etc. Therefore, this paper will review and explore various access controls implemented in a cloud environment that achieve different security purposes. The methodology followed in this survey was conducting an assessment, evaluation, and comparison between those access controls mechanisms and technologies based on different factors, such as the security goals it achieves, usability, and cost-effectiveness. This assessment resulted in the fact that the technology used in an access control affects the security goals it achieves as well as there is no one access control method that achieves all security goals. Consequently, such a comparison would help decision-makers to choose properly the access controls that meet their requirements.Keywords: Access controls, cloud computing, confidentiality, identity and access management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 712583 Laboratory Experimentation for Supporting Collaborative Working in Engineering Education over the Internet
Authors: S. Odeh, E. Abdelghani
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Collaborative working environments for distance education can be considered as a more generic form of contemporary remote labs. At present, the majority of existing real laboratories are not constructed to allow the involved participants to collaborate in real time. To make this revolutionary learning environment possible we must allow the different users to carry out an experiment simultaneously. In recent times, multi-user environments are successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat-text tools, multi-player games etc. Thus, understanding the ideas and techniques behind these systems could be of great importance in the contribution of ideas to our e-learning environment for collaborative working. In this investigation, collaborative working environments from theoretical and practical perspectives are considered in order to build an effective collaborative real laboratory, which allows two students or more to conduct remote experiments at the same time as a team. In order to achieve this goal, we have implemented distributed system architecture, enabling students to obtain an automated help by either a human tutor or a rule-based e-tutor.Keywords: Collaboration environment, e-tutor, multi-user environments, socio-technical system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1474582 Types of Epilepsies and Findings EEG- LORETA about Epilepsy
Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi
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Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review the findings EEG- LORETA about epilepsy.Keywords: Epilepsy, EEG, EEG- Loreta, loreta analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3081581 Methods for Material and Process Monitoring by Characterization of (Second and Third Order) Elastic Properties with Lamb Waves
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In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.
Keywords: Lamb waves, industry 4.0, process control, elasticity, acoustoelasticity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1085580 Searching for Forensic Evidence in a Compromised Virtual Web Server against SQL Injection Attacks and PHP Web Shell
Authors: Gigih Supriyatno
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SQL injection is one of the most common types of attacks and has a very critical impact on web servers. In the worst case, an attacker can perform post-exploitation after a successful SQL injection attack. In the case of forensics web servers, web server analysis is closely related to log file analysis. But sometimes large file sizes and different log types make it difficult for investigators to look for traces of attackers on the server. The purpose of this paper is to help investigator take appropriate steps to investigate when the web server gets attacked. We use attack scenarios using SQL injection attacks including PHP backdoor injection as post-exploitation. We perform post-mortem analysis of web server logs based on Hypertext Transfer Protocol (HTTP) POST and HTTP GET method approaches that are characteristic of SQL injection attacks. In addition, we also propose structured analysis method between the web server application log file, database application, and other additional logs that exist on the webserver. This method makes the investigator more structured to analyze the log file so as to produce evidence of attack with acceptable time. There is also the possibility that other attack techniques can be detected with this method. On the other side, it can help web administrators to prepare their systems for the forensic readiness.
Keywords: Web forensic, SQL injection, web shell, investigation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1244579 Adomian Decomposition Method Associated with Boole-s Integration Rule for Goursat Problem
Authors: Mohd Agos Salim Nasir, Ros Fadilah Deraman, Siti Salmah Yasiran
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The Goursat partial differential equation arises in linear and non linear partial differential equations with mixed derivatives. This equation is a second order hyperbolic partial differential equation which occurs in various fields of study such as in engineering, physics, and applied mathematics. There are many approaches that have been suggested to approximate the solution of the Goursat partial differential equation. However, all of the suggested methods traditionally focused on numerical differentiation approaches including forward and central differences in deriving the scheme. An innovation has been done in deriving the Goursat partial differential equation scheme which involves numerical integration techniques. In this paper we have developed a new scheme to solve the Goursat partial differential equation based on the Adomian decomposition (ADM) and associated with Boole-s integration rule to approximate the integration terms. The new scheme can easily be applied to many linear and non linear Goursat partial differential equations and is capable to reduce the size of computational work. The accuracy of the results reveals the advantage of this new scheme over existing numerical method.Keywords: Goursat problem, partial differential equation, Adomian decomposition method, Boole's integration rule.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1845578 Irrigation Water Quality Evaluation Based on Multivariate Statistical Analysis: A Case Study of Jiaokou Irrigation District
Authors: Panpan Xu, Qiying Zhang, Hui Qian
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Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K+, Na+, Mg2+, Ca2+, SO42-, Cl-, HCO3-, and CO32-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl-, Na+, Mg2+, and SO42-, and the HCO3- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.
Keywords: Irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 549577 A Novel Computer Vision Method for Evaluating Deformations of Fibers Cross Section in False Twist Textured Yarns
Authors: Dariush Semnani, Mehdi Ahangareianabhari, Hossein Ghayoor
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In recent five decades, textured yarns of polyester fiber produced by false twist method are the most important and mass-produced manmade fibers. There are many parameters of cross section which affect the physical and mechanical properties of textured yarns. These parameters are surface area, perimeter, equivalent diameter, large diameter, small diameter, convexity, stiffness, eccentricity, and hydraulic diameter. These parameters were evaluated by digital image processing techniques. To find trends between production criteria and evaluated parameters of cross section, three criteria of production line have been adjusted and different types of yarns were produced. These criteria are temperature, drafting ratio, and D/Y ratio. Finally the relations between production criteria and cross section parameters were considered. The results showed that the presented technique can recognize and measure the parameters of fiber cross section in acceptable accuracy. Also, the optimum condition of adjustments has been estimated from results of image analysis evaluation.Keywords: Computer Vision, Cross Section Analysis, Fibers Deformation, Textured Yarn
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1639576 An Efficient Motion Recognition System Based on LMA Technique and a Discrete Hidden Markov Model
Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier
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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 714575 Variability of Metal Composition and Concentrations in Road Dust in the Urban Environment
Authors: Sandya Mummullage, Prasanna Egodawatta, Ashantha Goonetilleke, Godwin A. Ayoko
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Urban road dust comprises of a range of potentially toxic metal elements and plays a critical role in degrading urban receiving water quality. Hence, assessing the metal composition and concentration in urban road dust is a high priority. This study investigated the variability of metal composition and concentrations in road dust in 4 different urban land uses in Gold Coast, Australia. Samples from 16 road sites were collected and tested for selected 12 metal species. The data set was analyzed using both univariate and multivariate techniques. Outcomes of the data analysis revealed that the metal concentrations inroad dust differs considerably within and between different land uses. Iron, aluminum, magnesium and zinc are the most abundant in urban land uses. It was also noted that metal species such as titanium, nickel, copper and zinc have the highest concentrations in industrial land use. The study outcomes revealed that soil and traffic related sources as key sources of metals deposited on road surfaces.
Keywords: Metals build-up, Pollutant accumulation, Stormwater quality, Urban road dust.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2337574 Using Analytic Hierarchy Process as a Decision-Making Tool in Project Portfolio Management
Authors: D. Danesh, M. J. Ryan, A. Abbasi
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Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findings in a mathematically meaningful manner that indicates the strategic significance of the associated projects at a number of levels of abstraction. PPM success is directly associated with the quality of decisions made and poor judgment increases portfolio costs. Hence, various Multi-Criteria Decision Making (MCDM) techniques have been designed and employed to support the decision-making functions. This paper reviews possible options to enhance the decision-making outcomes in organisational portfolio management processes using the Analytic Hierarchy Process (AHP) both from academic and practical perspectives and will examine the usability, certainty and quality of the technique. The results of the study will also provide insight into the technical risk associated with current decision-making model to underpin initiative tracking and strategic portfolio management.Keywords: Analytic hierarchy process, decision support systems, multi-criteria decision-making, project portfolio management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4253573 The Use of Hydrocolloid Dressing in the Management of Open Wounds in Big Cats
Authors: Catherine Portelli
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Felines, such as Panthera tigris, Panthera leo and Puma concolor, have become common residents in animal parks and zoos. They often sustain injuries from other felines within the same, or adjacent enclosures and from playing with items of enrichment and structures of the enclosure itself. These open wounds, and their treatments, are often challenging in veterinary practice, where feline-specific studies are lacking. This study is based on the author’s clinical experience gained while working at local animal parks in the past five years, and current evidence of hydrocolloid dressing applied to other species. Hydrocolloid dressing is used for secondary healing of chronic and acute wounds, where there is a considerable amount of tissue loss. The patients included in this study were sedated using medetomidine and ketamine every three to four days, for wound treatment and bandage change. Comparative studies of different techniques of open wound management will improve the healing process of exotic felines in the future by decreasing the time of recovery and incidence of other complications. Such studies will also aid with treatment of injuries sustained in wild felines, such as foot hold trap and bite wounds, found in natural conservation areas and wild animal sanctuaries.
Keywords: Felines, hydrocolloid dressing, open wound, secondary healing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 371572 Internal Power Recovery in Cryogenic Cooling Plants Part I: Expander Development
Authors: Ambra Giovannelli, Erika Maria Archilei
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The amount of the electrical power required by refrigeration systems is relevant worldwide. It is evaluated in the order of 15% of the total electricity production taking refrigeration and air-conditioning into consideration. For this reason, in the last years several energy saving techniques have been proposed to reduce the power demand of such plants. The paper deals with the development of an innovative internal recovery system for cryogenic cooling plants. Such a system consists in a Compressor-Expander Group (CEG) designed on the basis of the automotive turbocharging technology. In particular, the paper is focused on the design of the expander, the critical component of the CEG system. Due to the low volumetric flow entering the expander and the high expansion ratio, a commercial turbocharger expander wheel was strongly modified. It was equipped with a transonic nozzle, designed to have a radially inflow full admission. To verify the performance of such a machine and suggest improvements, two different set of nozzles have been designed and modelled by means of the commercial Ansys-CFX software. steady-state 3D CFD simulations of the second-generation prototype are presented and compared with the initial ones.
Keywords: Energy saving, organic fluids, radial turbine, refrigeration plant, vapor compression systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1210