Search results for: extraction of logical rules
179 The Problems of Legal Regulation of Intellectual Property Rights in Innovation Activities in Russia (Institutional Approach)
Authors: Zhanna Mingaleva, Irina Mirskikh
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Part IV of the Civil Code of the Russian Federation dedicated to legal regulation of Intellectual property rights came into force in 2008. It is a first attempt of codification in Intellectual property sphere in Russia. That is why a lot of new norms appeared. The main problem of the Russian Civil Code (part IV) is that many rules (norms of Law) contradict the norms of International Intellectual property Law (i.e. protection of inventions, creations, ideas, know-how, trade secrets, innovations). Intellectual property rights protect innovations and creations and reward innovative and creative activity. Intellectual property rights are international in character and in that respect they fit in rather well with the economic reality of the global economy. Inventors prefer not to take out a patent for inventions because it is a very difficult procedure, it takes a lot of time and is very expensive. That-s why they try to protect their inventions as ideas, know-how, confidential information. An idea is the main element of any object of Intellectual property (creation, invention, innovation, know-how, etc.). But ideas are not protected by Civil Code of Russian Federation. The aim of the paper is to reveal the main problems of legal regulation of Intellectual property in Russia and to suggest possible solutions. The authors of this paper have raised these essential issues through different activities. Through the panel survey, questionnaires which were spread among the participants of intellectual activities the main problems of implementation of innovations, protecting of the ideas and know-how were identified. The implementation of research results will help to solve economic and legal problems of innovations, transfer of innovations and intellectual property.1
Keywords: Innovation activities, intellectual property rights, know-how, patents, indicators of innovation activities
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1508178 A Novel Approach for Protein Classification Using Fourier Transform
Authors: A. F. Ali, D. M. Shawky
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Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.
Keywords: Bioinformatics, Artificial Neural Networks, Protein Sequence Analysis, Feature Extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2343177 Intelligent Video-Based Monitoring of Freeway Traffic
Authors: Saad M. Al-Garni, Adel A. Abdennour
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Freeways are originally designed to provide high mobility to road users. However, the increase in population and vehicle numbers has led to increasing congestions around the world. Daily recurrent congestion substantially reduces the freeway capacity when it is most needed. Building new highways and expanding the existing ones is an expensive solution and impractical in many situations. Intelligent and vision-based techniques can, however, be efficient tools in monitoring highways and increasing the capacity of the existing infrastructures. The crucial step for highway monitoring is vehicle detection. In this paper, we propose one of such techniques. The approach is based on artificial neural networks (ANN) for vehicles detection and counting. The detection process uses the freeway video images and starts by automatically extracting the image background from the successive video frames. Once the background is identified, subsequent frames are used to detect moving objects through image subtraction. The result is segmented using Sobel operator for edge detection. The ANN is, then, used in the detection and counting phase. Applying this technique to the busiest freeway in Riyadh (King Fahd Road) achieved higher than 98% detection accuracy despite the light intensity changes, the occlusion situations, and shadows.Keywords: Background Extraction, Neural Networks, VehicleDetection, Freeway Traffic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1898176 Critical Approach to Define the Architectural Structure of a Health Prototype in a Rural Area of Brazil
Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Luca Preis
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A primary healthcare facility in developing countries should be a multifunctional space able to respond to different requirements: Flexibility, modularity, aggregation and reversibility. These basic features could be better satisfied if applied to an architectural artifact that complies with the typological, figurative and constructive aspects of the context in which it is located. Therefore, the purpose of this paper is to identify a procedure that can define the figurative aspects of the architectural structure of the health prototype for the marginal areas of developing countries through a critical approach. The application context is the rural areas of the Northeast of Bahia in Brazil. The prototype should be located in the rural district of Quingoma, in the municipality of Lauro de Freitas, a particular place where there is still a cultural fusion of black and indigenous populations. Based on the historical analysis of settlement strategies and architectural structures in spaces of public interest or collective use, this paper aims to provide a procedure able to identify the categories and rules underlying typological and figurative aspects, in order to detect significant and generalizable elements, as well as materials and constructive techniques typically adopted in the rural areas of Brazil. The object of this work is therefore not only the recovery of certain constructive approaches but also the development of a procedure that integrates the requirements of the primary healthcare prototype with its surrounding economic, social, cultural, settlement and figurative conditions.Keywords: Architectural typology, Developing countries, Local construction techniques, Primary health care.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 927175 High-Accuracy Satellite Image Analysis and Rapid DSM Extraction for Urban Environment Evaluations (Tripoli-Libya)
Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves
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Modelling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve more dense and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.
Keywords: 3D Models, Environment, Matching, Pleiades.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2678174 The Correlation of Total Phenol Content with Free Radicals Scavenging Activity and Effect of Ethanol Concentration in Extraction Process of Mangosteen Rind (Garcinia mangostana)
Authors: Ririn Lestari Sri Rahayu, Mustofa Ahda
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The use of synthetic antioxidants often causes a negative effect on health and increases the incidence of carcinogenesis. Development of the natural antioxidants should be investigated. However, natural antioxidants have a low toxicity and are safe for human consumption. Ethanol extract of mangosteen rind (Garcinia mangostana) contains natural antioxidant compounds that have various pharmacological activities. Antioxidants from the ethanol extract of mangosteen rind have free radicals scavenging activities. The scavenging activity of ethanol extract of mangosteen rind was determined by DPPH method. The phenolic compound from the ethanol extract of mangosteen rind is determined with Folin-Ciocalteu method. The results showed that the absolute ethanol extract of mangosteen rind has IC50 of 40.072 ug/mL. The correlation of total phenols content with free radical scavenging activity has an equation y: 5.207x + 205.51 and determination value (R2) of 0.9329. Total phenols content from the ethanol extract of mangosteen rind has a good correlation with free radicals scavenging activity of DPPH.
Keywords: Antioxidant, Garcinia mangostana, inhibition concentration 50%, total phenolic compounds.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1287173 Validation and Application of a New Optimized RP-HPLC-Fluorescent Detection Method for Norfloxacin
Authors: Mahmood Ahmad, Ghulam Murtaza, Sonia Khiljee, Muhammad Asadullah Madni
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A new reverse phase-high performance liquid chromatography (RP-HPLC) method with fluorescent detector (FLD) was developed and optimized for Norfloxacin determination in human plasma. Mobile phase specifications, extraction method and excitation and emission wavelengths were varied for optimization. HPLC system contained a reverse phase C18 (5 μm, 4.6 mm×150 mm) column with FLD operated at excitation 330 nm and emission 440 nm. The optimized mobile phase consisted of 14% acetonitrile in buffer solution. The aqueous phase was prepared by mixing 2g of citric acid, 2g sodium acetate and 1 ml of triethylamine in 1 L of Milli-Q water was run at a flow rate of 1.2 mL/min. The standard curve was linear for the range tested (0.156–20 μg/mL) and the coefficient of determination was 0.9978. Aceclofenac sodium was used as internal standard. A detection limit of 0.078 μg/mL was achieved. Run time was set at 10 minutes because retention time of norfloxacin was 0.99 min. which shows the rapidness of this method of analysis. The present assay showed good accuracy, precision and sensitivity for Norfloxacin determination in human plasma with a new internal standard and can be applied pharmacokinetic evaluation of Norfloxacin tablets after oral administration in human.
Keywords: Norfloxacin, Aceclofenac sodium, Methodoptimization, RP-HPLC method, Fluorescent detection, Calibrationcurve.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2091172 Image Indexing Using a Color Similarity Metric based on the Human Visual System
Authors: Angelo Nodari, Ignazio Gallo
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The novelty proposed in this study is twofold and consists in the developing of a new color similarity metric based on the human visual system and a new color indexing based on a textual approach. The new color similarity metric proposed is based on the color perception of the human visual system. Consequently the results returned by the indexing system can fulfill as much as possibile the user expectations. We developed a web application to collect the users judgments about the similarities between colors, whose results are used to estimate the metric proposed in this study. In order to index the image's colors, we used a text indexing engine to facilitate the integration of visual features in a database of text documents. The textual signature is build by weighting the image's colors in according to their occurrence in the image. The use of a textual indexing engine, provide us a simple, fast and robust solution to index images. A typical usage of the system proposed in this study, is the development of applications whose data type is both visual and textual. In order to evaluate the proposed method we chose a price comparison engine as a case of study, collecting a series of commercial offers containing the textual description and the image representing a specific commercial offer.
Keywords: Color Extraction, Content-Based Image Retrieval, Indexing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3016171 Hybrid Structure Learning Approach for Assessing the Phosphate Laundries Impact
Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed
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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).
Keywords: Classification, Bayesian network; structure learning, K2 algorithm, expert knowledge, surface water analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 498170 Use of Social Media in PR: A Change of Trend
Authors: Tang Mui Joo, Chan Eang Teng
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The use of social media has become more defined. It has been widely used for the purpose of business. More marketers are now using social media as tools to enhance their businesses. Whereas on the other hand, there are more and more people spending their time through mobile apps to be engaged in the social media sites like YouTube, Facebook, Twitter and others. Social media has even become common in Public Relations (PR). It has become number one platform for creating and sharing content. In view to this, social media has changed the rules in PR where it brings new challenges and opportunities to the profession. Although corporate websites, chat-rooms, email customer response facilities and electronic news release distribution are now viewed as standard aspects of PR practice, many PR practitioners are still struggling with the impact of new media though the implementation of social media is potentially reducing the cost of communication. It is to the point that PR practitioners are not fully embracing new media, they are ill-equipped to do so and they have a fear of the technology. Somehow that social media has become a new style of communication that is characterized by conversation and community. It has become a platform that allows individuals to interact with one another and build relationship among each other. Therefore, in the use of business world, consumers are able to interact with those companies that have joined any social media. Based on their experiences with social networking site interactions, they are also exposed to personal interaction while communicating. This paper is to study the impact of social media to PR. This paper discovers the potential changes of PR practices in a developing country like Malaysia. Eventually the study reflects on how PR practitioners are actually using social media in the country. This paper is based on two theories in its development of this research foundation. Media Ecology Theory is to support the impact and changes to PR. Social Penetration Theory is to reflect on how the use of social media is among PRs. This research is using survey with PR practitioners in its data collection. The results have shown that PR professionals value social media more than they actually use it and the way of organizations communicate had been changed due to the transformation of social media.Keywords: New media, social media, PR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6066169 A Ground Structure Method to Minimize the Total Installed Cost of Steel Frame Structures
Authors: Filippo Ranalli, Forest Flager, Martin Fischer
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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.
Keywords: Cost-based structural optimization, cost-based topology and sizing optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1400168 Improvement of Model for SIMMER Code for SFR Corium Relocation Studies
Authors: A. Bachrata, N. Marie, F. Bertrand, J. B. Droin
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The in-depth understanding of severe accident propagation in Generation IV of nuclear reactors is important so that appropriate risk management can be undertaken early in their design process. This paper is focused on model improvements in the SIMMER code in order to perform studies of severe accident mitigation of Sodium Fast Reactor. During the design process of the mitigation devices dedicated to extraction of molten fuel from the core region, the molten fuel propagation from the core up to the core catcher has to be studied. In this aim, analytical as well as the complex thermohydraulic simulations with SIMMER-III code are performed. The studies presented in this paper focus on physical phenomena and associated physical models that influence the corium relocation. Firstly, the molten pool heat exchange with surrounding structures is analyzed since it influences directly the instant of rupture of the dedicated tubes favoring the corium relocation for mitigation purpose. After the corium penetration into mitigation tubes, the fuel-coolant interactions result in formation of debris bed. Analyses of debris bed fluidization as well as sinking into a fluid are presented in this paper.
Keywords: Corium, mitigation tubes, SIMMER-III, sodium fast reactor (SFR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2867167 The Tyrosinase and Cyclooxygenase Inhibitory Activities and Cytotoxicity Screening of Tamarindus indica Seeds
Authors: P. Thongmuang, Y. Sudjaroen
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The methanolic extracts from seeds of tamarind (Tamarindus indica) was prepared by Soxhlet apparatus extraction and evaluated for total phenolic content by Folin-Ciocalteu method. Then, methanolic extract was screened biological activities (In vitro) for anti-melanogenic activity by tyrosinase inhibition test, antiinflammation activity by cyclooxygenase 1 (COX-1) and cyclooxygenase 2 (COX-2) inhibition test, and cytotoxic screening test with Vero cells. The results showed that total phenolic content, which contained in extract, was contained 27.72 mg of gallic acid equivalent per g of dry weight. The ability to inhibit tyrosinase enzyme, which exerted by Tamarind seed extracts (1 mg/ml) was 52.13 ± 0.42 %. The extract was not possessed inhibitory effect to COX-1 and COX-2 enzymes and cytotoxic effect to Vero cells. The finding is concludes that tested seed extract was possessed antimelanogenic activity with non-toxic effects. However, there was not exhibited anti-inflammatory activity. Further studies include the use of advance biological models to confirm this biological activity, as well as, the isolation and characterization of the purified compounds that it was contained.Keywords: Tamarindus indica, anti-melanogenic, antiinflammatotion, cytotoxicity, seed, phenolic compounds.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2924166 Novel Use of a Quality Assurance Tool for Integrating Technology to HSE
Authors: Ragi Poyyara, Vivek V., Ashish Khaparde
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The product development process (PDP) in the Technology group plays a very important role in the launch of any product. While a manufacturing process encourages the use of certain measures to reduce health, safety and environmental (HSE) risks on the shop floor, the PDP concentrates on the use of Geometric Dimensioning and Tolerancing (GD&T) to develop a flawless design. Furthermore, PDP distributes and coordinates activities between different departments such as marketing, purchasing, and manufacturing. However, it is seldom realized that PDP makes a significant contribution to developing a product that reduces HSE risks by encouraging the Technology group to use effective GD&T. The GD&T is a precise communication tool that uses a set of symbols, rules, and definitions to mathematically define parts to be manufactured. It is a quality assurance method widely used in the oil and gas sector. Traditionally it is used to ensure the interchangeability of a part without affecting its form, fit, and function. Parts that do not meet these requirements are rejected during quality audits. This paper discusses how the Technology group integrates this quality assurance tool into the PDP and how the tool plays a major role in helping the HSE department in its goal towards eliminating HSE incidents. The PDP involves a thorough risk assessment and establishes a method to address those risks during the design stage. An illustration shows how GD&T helped reduce safety risks by ergonomically improving assembling operations. A brief discussion explains how tolerances provided on a part help prevent finger injury. This tool has equipped Technology to produce fixtures, which are used daily in operations as well as manufacturing. By applying GD&T to create good fits, HSE risks are mitigated for operating personnel. Both customers and service providers benefit from reduced safety risks.
Keywords: HSE, PDP, GD&T, risks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1822165 Criminal Justice System, Health and Imprisonment in India
Authors: Debolina Chatterjee, Suhita Chopra Chatterjee
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Imprisonment is an expansive concept, as it is regulated by laws under criminal justice system of the state. The state sets principles of punishment to control offenders and also puts limits to excess punitive control. One significant way through which it exercises control is through rules governing healthcare of imprisoned population. Prisons signify specialized settings which accommodate both medical and legal concerns. The provision of care operates within the institutional paradigm of punishment. This requires the state to negotiate adequately between goals of punishment and fulfilment of basic human rights of offenders. The present study is based on a critical analysis of prison healthcare standards in India, which include government policies and guidelines. It also demonstrates how healthcare is delivered by drawing insights from a primary study conducted in a correctional home in the state of West Bengal, India, which houses both male and female inmates. Forty women were interviewed through semi-structured interviews, followed by focus group discussions. Doctors and administrative personnel were also interviewed. Findings show how institutional practices control women through subversion of the role of doctors to prison administration. Also, poor healthcare infrastructure, unavailability of specialized services, hierarchies between personnel and inmates make prisons unlikely sites for therapeutic intervention. The paper further discusses how institutional practices foster gender-based discriminatory practices.Keywords: Imprisonment, imprisoned women, prison healthcare, prison policies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1283164 View-Point Insensitive Human Pose Recognition using Neural Network
Authors: Sanghyeok Oh, Yunli Lee, Kwangjin Hong, Kirak Kim, Keechul Jung
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This paper proposes view-point insensitive human pose recognition system using neural network. Recognition system consists of silhouette image capturing module, data driven database, and neural network. The advantages of our system are first, it is possible to capture multiple view-point silhouette images of 3D human model automatically. This automatic capture module is helpful to reduce time consuming task of database construction. Second, we develop huge feature database to offer view-point insensitivity at pose recognition. Third, we use neural network to recognize human pose from multiple-view because every pose from each model have similar feature patterns, even though each model has different appearance and view-point. To construct database, we need to create 3D human model using 3D manipulate tools. Contour shape is used to convert silhouette image to feature vector of 12 degree. This extraction task is processed semi-automatically, which benefits in that capturing images and converting to silhouette images from the real capturing environment is needless. We demonstrate the effectiveness of our approach with experiments on virtual environment.Keywords: Computer vision, neural network, pose recognition, view-point insensitive.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1318163 A Tuning Method for Microwave Filter via Complex Neural Network and Improved Space Mapping
Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu
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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.Keywords: Microwave filter, scattering parameter (s-parameter), coupling matrix, intelligent tuning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1300162 Recommended Practice for Experimental Evaluation of the Seepage Sensitivity Damage of Coalbed Methane Reservoirs
Authors: Hao Liu, Lihui Zheng, Chinedu J. Okere, Chao Wang, Xiangchun Wang, Peng Zhang
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The coalbed methane (CBM) extraction industry (an unconventional energy source) has not established guidelines for experimental evaluation of sensitivity damage for coal samples. The existing experimental process of previous researches mainly followed the industry standard for conventional oil and gas reservoirs (CIS). However, the existing evaluation method ignores certain critical differences between CBM reservoirs and conventional reservoirs, which could inevitably result in an inaccurate evaluation of sensitivity damage and, eventually, poor decisions regarding the formulation of formation damage prevention measures. In this study, we propose improved experimental guidelines for evaluating seepage sensitivity damage of CBM reservoirs by leveraging on the shortcomings of the existing methods. The proposed method was established via a theoretical analysis of the main drawbacks of the existing methods and validated through comparative experiments. The results show that the proposed evaluation technique provided reliable experimental results that can better reflect actual reservoir conditions and correctly guide the future development of CBM reservoirs. This study is pioneering the research on the optimization of experimental parameters for efficient exploration and development of CBM reservoirs.
Keywords: Coalbed methane, formation damage, permeability, unconventional energy source.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 363161 An Adaptive Dimensionality Reduction Approach for Hyperspectral Imagery Semantic Interpretation
Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman
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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.Keywords: Band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1163160 ANN Based Currency Recognition System using Compressed Gray Scale and Application for Sri Lankan Currency Notes - SLCRec
Authors: D. A. K. S. Gunaratna, N. D. Kodikara, H. L. Premaratne
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Automatic currency note recognition invariably depends on the currency note characteristics of a particular country and the extraction of features directly affects the recognition ability. Sri Lanka has not been involved in any kind of research or implementation of this kind. The proposed system “SLCRec" comes up with a solution focusing on minimizing false rejection of notes. Sri Lankan currency notes undergo severe changes in image quality in usage. Hence a special linear transformation function is adapted to wipe out noise patterns from backgrounds without affecting the notes- characteristic images and re-appear images of interest. The transformation maps the original gray scale range into a smaller range of 0 to 125. Applying Edge detection after the transformation provided better robustness for noise and fair representation of edges for new and old damaged notes. A three layer back propagation neural network is presented with the number of edges detected in row order of the notes and classification is accepted in four classes of interest which are 100, 500, 1000 and 2000 rupee notes. The experiments showed good classification results and proved that the proposed methodology has the capability of separating classes properly in varying image conditions.Keywords: Artificial intelligence, linear transformation and pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2820159 Improved Fuzzy Neural Modeling for Underwater Vehicles
Authors: O. Hassanein, Sreenatha G. Anavatti, Tapabrata Ray
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The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line adaptive fuzzy model and adaptive neural fuzzy network (ANFN) model techniques to overcome the uncertain external disturbance and the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according to the back propagation algorithm based upon the error between the identified model and the actual output of the plant. The proposed ANFN model adopts a functional link neural network (FLNN) as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN model is a nonlinear combination of input variables. Fuzzy control system is applied to guide and control the AUV using both adaptive models and mathematical model. Simulation results show the superiority of the proposed adaptive neural fuzzy network (ANFN) model in tracking of the behavior of the AUV accurately even in the presence of noise and disturbance.Keywords: AUV, AUV dynamic model, fuzzy control, fuzzy modelling, adaptive fuzzy control, back propagation, system identification, neural fuzzy model, FLNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2144158 A Fuzzy MCDM Approach for Health-Care Waste Management
Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi
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The management of the health-care wastes is one of the most important problems in Istanbul, a city with more than 12 million inhabitants, as it is in most of the developing countries. Negligence in appropriate treatment and final disposal of the healthcare wastes can lead to adverse impacts to public health and to the environment. This paper employs a fuzzy multi-criteria group decision making approach, which is based on the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and technique for order preference by similarity to ideal solution (TOPSIS), to evaluate health-care waste (HCW) treatment alternatives for Istanbul. The evaluation criteria are determined employing nominal group technique (NGT), which is a method of systematically developing a consensus of group opinion. The employed method is apt to manage information assessed using multigranularity linguistic information in a decision making problem with multiple information sources. The decision making framework employs ordered weighted averaging (OWA) operator that encompasses several operators as the aggregation operator since it can implement different aggregation rules by changing the order weights. The aggregation process is based on the unification of information by means of fuzzy sets on a basic linguistic term set (BLTS). Then, the unified information is transformed into linguistic 2-tuples in a way to rectify the problem of loss information of other fuzzy linguistic approaches.Keywords: Group decision making, health care waste management, multi-criteria decision making, OWA, TOPSIS, 2-tuple linguistic representation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2391157 Recognizing an Individual, Their Topic of Conversation, and Cultural Background from 3D Body Movement
Authors: Gheida J. Shahrour, Martin J. Russell
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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that intersubject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.
Keywords: Person Recognition, Topic Recognition, Culture Recognition, 3D Body Movement Signals, Variability Compensation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2164156 Automatic Removal of Ocular Artifacts using JADE Algorithm and Neural Network
Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss
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The ElectroEncephaloGram (EEG) is useful for clinical diagnosis and biomedical research. EEG signals often contain strong ElectroOculoGram (EOG) artifacts produced by eye movements and eye blinks especially in EEG recorded from frontal channels. These artifacts obscure the underlying brain activity, making its visual or automated inspection difficult. The goal of ocular artifact removal is to remove ocular artifacts from the recorded EEG, leaving the underlying background signals due to brain activity. In recent times, Independent Component Analysis (ICA) algorithms have demonstrated superior potential in obtaining the least dependent source components. In this paper, the independent components are obtained by using the JADE algorithm (best separating algorithm) and are classified into either artifact component or neural component. Neural Network is used for the classification of the obtained independent components. Neural Network requires input features that exactly represent the true character of the input signals so that the neural network could classify the signals based on those key characters that differentiate between various signals. In this work, Auto Regressive (AR) coefficients are used as the input features for classification. Two neural network approaches are used to learn classification rules from EEG data. First, a Polynomial Neural Network (PNN) trained by GMDH (Group Method of Data Handling) algorithm is used and secondly, feed-forward neural network classifier trained by a standard back-propagation algorithm is used for classification and the results show that JADE-FNN performs better than JADEPNN.Keywords: Auto Regressive (AR) Coefficients, Feed Forward Neural Network (FNN), Joint Approximation Diagonalisation of Eigen matrices (JADE) Algorithm, Polynomial Neural Network (PNN).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1877155 Cytotoxic Effect of Crude Extract of Sea Pen Virgularia gustaviana on HeLa and MDA-MB-231 Cancer Cell Lines
Authors: Sharareh Sharifi, Pargol Ghavam Mostafavi, Ali Mashinchian Moradi, Mohammad Hadi Givianrad, Hassan Niknejad
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Marine organisms such as soft coral, sponge, ascidians, and tunicate containing rich source of natural compound have been studied in last decades because of their special chemical compounds with anticancer properties. The aim of this study was to investigate anti-cancer property of ethyl acetate extracted from marine sea pen Virgularia gustaviana found from Persian Gulf coastal (Bandar Abbas). The extraction processes were carried out with ethyl acetate for five days. Thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC) were used for qualitative identification of crude extract. The viability of HeLa and MDA-Mb-231 cancer cells was investigated using MTT assay at the concentration of 25, 50, and a 100 µl/ml of ethyl acetate is extracted. The crude extract of Virgularia gustaviana demonstrated ten fractions with different Retention factor (Rf) by TLC and Retention time (Rt) evaluated by HPLC. The crude extract dose-dependently decreased cancer cell viability compared to control group. According to the results, the ethyl acetate extracted from Virgularia gustaviana inhibits the growth of cancer cells, an effect which needs to be further investigated in the future studies.Keywords: Virgularia gustaviana, Cembrane Diterpene, anti-cancer, HeLa cancer Cell, MDA-Md-231 Cancer cell.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1534154 Speaker Identification using Neural Networks
Authors: R.V Pawar, P.P.Kajave, S.N.Mali
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The speech signal conveys information about the identity of the speaker. The area of speaker identification is concerned with extracting the identity of the person speaking the utterance. As speech interaction with computers becomes more pervasive in activities such as the telephone, financial transactions and information retrieval from speech databases, the utility of automatically identifying a speaker is based solely on vocal characteristic. This paper emphasizes on text dependent speaker identification, which deals with detecting a particular speaker from a known population. The system prompts the user to provide speech utterance. System identifies the user by comparing the codebook of speech utterance with those of the stored in the database and lists, which contain the most likely speakers, could have given that speech utterance. The speech signal is recorded for N speakers further the features are extracted. Feature extraction is done by means of LPC coefficients, calculating AMDF, and DFT. The neural network is trained by applying these features as input parameters. The features are stored in templates for further comparison. The features for the speaker who has to be identified are extracted and compared with the stored templates using Back Propogation Algorithm. Here, the trained network corresponds to the output; the input is the extracted features of the speaker to be identified. The network does the weight adjustment and the best match is found to identify the speaker. The number of epochs required to get the target decides the network performance.Keywords: Average Mean Distance function, Backpropogation, Linear Predictive Coding, MultilayeredPerceptron,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1885153 Fused Structure and Texture (FST) Features for Improved Pedestrian Detection
Authors: Hussin K. Ragb, Vijayan K. Asari
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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.Keywords: Pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1481152 Teager-Huang Analysis Applied to Sonar Target Recognition
Authors: J.-C. Cexus, A.O. Boudraa
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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.
Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2269151 Feature Based Dense Stereo Matching using Dynamic Programming and Color
Authors: Hajar Sadeghi, Payman Moallem, S. Amirhassn Monadjemi
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This paper presents a new feature based dense stereo matching algorithm to obtain the dense disparity map via dynamic programming. After extraction of some proper features, we use some matching constraints such as epipolar line, disparity limit, ordering and limit of directional derivative of disparity as well. Also, a coarseto- fine multiresolution strategy is used to decrease the search space and therefore increase the accuracy and processing speed. The proposed method links the detected feature points into the chains and compares some of the feature points from different chains, to increase the matching speed. We also employ color stereo matching to increase the accuracy of the algorithm. Then after feature matching, we use the dynamic programming to obtain the dense disparity map. It differs from the classical DP methods in the stereo vision, since it employs sparse disparity map obtained from the feature based matching stage. The DP is also performed further on a scan line, between any matched two feature points on that scan line. Thus our algorithm is truly an optimization method. Our algorithm offers a good trade off in terms of accuracy and computational efficiency. Regarding the results of our experiments, the proposed algorithm increases the accuracy from 20 to 70%, and reduces the running time of the algorithm almost 70%.Keywords: Chain Correspondence, Color Stereo Matching, Dynamic Programming, Epipolar Line, Stereo Vision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2335150 Integration of Image and Patient Data, Software and International Coding Systems for Use in a Mammography Research Project
Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst
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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1935