Search results for: feature analysis

Authors: Goutham Kumar Dogiparti, D. R. Seshu

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In the present study, wavelet analysis was used for locating damage in simply supported and cantilever beams. Study was carried out varying different levels and locations of damage. In numerical method, ANSYS software was used for modal analysis of damaged and undamaged beams. The mode shapes obtained from numerical analysis is processed using MATLAB wavelet toolbox to locate damage. Effect of several parameters such as (damage level, location) on the natural frequencies and mode shapes were also studied. The results indicated the potential of wavelets in identifying the damage location.

Keywords: damage, detection, beams, wavelets

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Authors: Renu Tomar, Hitendra K. Malik, Raj P. Dahiya

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Similar to the sound waves in air, plasmas support the propagation of ion waves, which evolve into the solitary structures when the effect of non linearity and dispersion are balanced. The ion acoustic solitary waves have been investigated in details in homogeneous plasmas, inhomogeneous plasmas, and magnetized plasmas. The ion acoustic solitary waves are also found to reflect from a density gradient or boundary present in the plasma after propagating. Another interesting feature of the solitary waves is their collision. In the present work, we carry out analytical calculations for the head-on collision of solitary waves in a magnetized plasma which has dust grains in addition to the ions and electrons. For this, we employ Poincar´e-Lighthill-Kuo (PLK) method. To lowest nonlinear order, the problem of colliding solitary waves leads to KdV (modified KdV) equations and also yields the phase shifts that occur in the interaction. These calculations are accomplished for the uniform and nonuniform plasmas, and the results on the soliton properties are discussed in detail.

Keywords: inhomogeneous magnetized plasma, dust charging, soliton collisions, magnetized plasma

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Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

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Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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Authors: Hromada Martin

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Risk analysis is considered as a fundamental aspect relevant for ensuring the level of critical infrastructure protection, where the critical infrastructure is seen as system, asset or its part which is important for maintaining the vital societal functions. Article actually discusses and analyzes the potential application of selected tools of information support for the implementation and within the framework of risk analysis and critical infrastructure protection. Use of the information in relation to their risk analysis can be viewed as a form of simplifying the analytical process. It is clear that these instruments (information support) for these purposes are countless, so they were selected representatives who have already been applied in the selected area of critical infrastructure, or they can be used. All presented fact were the basis for critical infrastructure resilience evaluation methodology development.

Keywords: critical infrastructure, protection, resilience, risk analysis

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Authors: Martin Surya Mulyadi, Yunita Anwar, Rosinta Ria Panggabean

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Major transformations in economic activity from an agricultural economy to knowledge economy have led to an increasing focus on intellectual capital (IC) that has been characterized by continuous innovation, the spread of digital and communication technologies, intangible and human factors. IC is defined as the possession of knowledge and experience, professional knowledge and skill, proper relationships and technological capacities, which when applied will give organizations a competitive advantage. All of IC report/disclosure could be captured from the corporate annual report as it is a communication device that allows a corporation to connect with various external and internal stakeholders. This study was conducted using sentence-content analysis of IC disclosure in the annual report. This research aims to analyze whether the keyword-content analysis is reliable research methodology for IC disclosure related research.

Keywords: intellectual capital, intellectual capital disclosure, content analysis, annual report, sentence analysis, keyword analysis

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Authors: Zdeněk Veselý, Milan Honner, Jiří Mach

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The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. The complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from the 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on the temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source

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Authors: Chao Xu

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Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.

Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis

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Authors: Tomáš Ludík, Jiří Barta, Sabina Chytilová, Josef Navrátil

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Emergency management is a discipline of dealing with and avoiding risks. Appropriate emergency management software allows better management of these risks and has a direct influence on reducing potential negative impacts. Although there are several emergency management software products in the Czech Republic, they cover user requirements from the emergency management field only partially. Therefore, the paper focuses on the issues of requirement analysis within development of emergency management software. Analysis of the current state describes the basic features and properties of user requirements for software development as well as basic methods and approaches for gathering these requirements. Then, the paper presents more specific mechanisms for requirement analysis based on chosen software development approach: structured, object-oriented or agile. Based on these experiences it is designed new methodology for requirement analysis. Methodology describes how to map user requirements comprehensively in the field of emergency management and thus reduce misunderstanding between software analyst and emergency manager. Proposed methodology was consulted with department of fire brigade and also has been applied in the requirements analysis for their current emergency management software. The proposed methodology has general character and can be used also in other specific areas during requirement analysis.

Keywords: emergency software, methodology, requirement analysis, stakeholders, use case diagram, user stories

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv

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The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.

Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, pareto analysis, RPN (Risk Priority Number)

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Aliyu Isah Agaie, Masrah Azrifah Azmi Murad, Nurfadhlina Mohd Sharef, Aida Mustapha

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Natural Language Interfaces typically support a restricted language and also have scopes and limitations that naïve users are unaware of, resulting in errors when the users attempt to retrieve information from ontologies. To overcome this challenge, an auto-suggest feature is introduced into the querying process where users are guided through the querying process using interactive query construction system. Guiding users to formulate their queries, while providing them with an unconstrained (or almost unconstrained) way to query the ontology results in better interpretation of the query and ultimately lead to an effective search. The approach described in this paper is unobtrusive and subtly guides the users, so that they have a choice of either selecting from the suggestion list or typing in full. The user is not coerced into accepting system suggestions and can express himself using fragments or full sentences.

Keywords: auto-suggest, expressiveness, habitability, natural language interface, query interpretation, user guidance

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Authors: Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan

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Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy.

Keywords: email marketing, email content, reinforcement learning, machine learning, Q-learning

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Authors: N. F. Hanna, A. M. Haridy

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One of the main drawbacks of the Modal Pushover Analysis (MPA) is the need to perform nonlinear time-history analysis, which complicates the analysis method and time. A simplified version of the MPA has been proposed based on the concept of the inelastic deformation ratio. Furthermore, the effect of the higher modes of vibration is considered by assuming linearly-elastic responses, which enables the use of standard elastic response spectrum analysis. In this thesis, the simplified MPA (SMPA) method is applied to determine the target global drift and the inter-story drifts of steel frame building. The effect of the higher vibration modes is considered within the framework of the SMPA. A comprehensive survey about the inelastic deformation ratio is presented. After that, a suitable expression from literature is selected for the inelastic deformation ratio and then implemented in the SMPA. The estimated seismic demands using the SMPA, such as target drift, base shear, and the inter-story drifts, are compared with the seismic responses determined by applying the standard MPA. The accuracy of the estimated seismic demands is validated by comparing with the results obtained by the nonlinear time-history analysis using real earthquake records.

Keywords: modal analysis, pushover analysis, seismic performance, target displacement

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Authors: B. Engel, Sara Salman Hassan Al-Maeeni

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Human consumption of the Earth's resources increases the need for a sustainable development as an important ecological, social, and economic theme. Re-engineering of machine tools, in terms of design and failure analysis, is defined as steps performed on an obsolete machine to return it to a new machine with the warranty that matches the customer requirement. To understand the future fatigue behavior of the used machine components, it is important to investigate the possible causes of machine parts failure through design, surface, and material inspections. In this study, the failure modes of the shaft of the rotary draw bending machine are inspected. Furthermore, stress and deflection analysis of the shaft subjected to combined torsion and bending loads are carried out by an analytical method and compared with a finite element analysis method. The theoretical fatigue strength, correction factors, and fatigue life sustained by the shaft before damaged are estimated by creating a stress-cycle (S-N) diagram. In conclusion, it is seen that the shaft can work in the second life, but it needs some surface treatments to increase the reliability and fatigue life.

Keywords: failure analysis, fatigue life, FEM analysis, shaft, stress analysis

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.

Keywords: document analysis, sentimental analysis, emotion detection, WEKA tool, NRC lexicon

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Authors: Nurdan Tumbek Tekeoglu

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With rising importance in all over the world, crowdfunding has become a new financing and marketing method for film industry. Crowdfunding is a new practice in film industry for funding a film project by raising monetary contributions from a large group of people. By crowdfunding an estimate fund of 20 billion USD has been raised in 2015. Through the crowdfunding platforms not only the film makers, but also the entrepreneurs and nongovernmental organizations finance and market their projects. Among the prominent crowdfunding platforms in Turkey, we can list Crowdfon, Fonlabeni, Kickstarter, Indiego, Bi Ayda, and Fongogo platforms. In 2014 the Turkish film industry celebrated its 100th anniversary and reached its peak producing around 150-200 films a year reminding the brilliant years of Yesilcam period. In general feature films apply for crowdfunding. Until April 2015 more than 190 films applied for crowdfunding platforms. Crowdfunding has a promising future in Turkey, since donation traditions has an important place in Turkish culture traditionally. This paper is exploring the marketing of the crowdfunding platforms established in Turkey in order for the films meet their target groups during the pre-production period.

Keywords: crowdfunding, marketing of films, Turkey, Turkish film industry

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Authors: Bela Lebedeva

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Characteristics of the Web as a channel of information dissemination - accessibility and openness, interactivity and multimedia news - become wider and cover the audience quickly, positively affecting the perception of content, but blur out the understanding of the journalistic work. As a result audience and advertisers continue migrating to the Internet. Moreover, online targeting allows monetizing not only the audience (as customarily given to traditional media) but also the content and traffic more accurately. While the users identify themselves with the qualitative characteristics of the new market, its actors are formed. Conflict of interests is laid in the base of the economy of their relations, the problem of traffic tax as an example. Meanwhile, content monetization actualizes fiscal interest of the state too. The balance of supply and demand is often violated due to the political risks, particularly in terms of state capitalism, populism and authoritarian methods of governance such social institutions as the media. A unique example of access to journalistic material, limited by monetization of content is a television channel Dozhd' (Rain) in Russian web space. Its liberal-minded audience has a better possibility for discussion. However, the channel could have been much more successful in terms of unlimited free speech. Avoiding state pressure and censorship its management has decided to save at least online performance and monetizing all of the content for the core audience. The study Methodology was primarily based on the analysis of journalistic content, on the qualitative and quantitative analysis of the audience. Reconstructing main events and relationships of actors on the market for the last six years researcher has reached some conclusions. First, under the condition of content monetization the capitalization of its quality will always strive to quality characteristics of user, thereby identifying him. Vice versa, the user's demand generates high-quality journalism. The second conclusion follows the previous one. The growth of technology, information noise, new political challenges, the economy volatility and the cultural paradigm change – all these factors form the content paying model for an individual user. This model defines him as a beneficiary of specific knowledge and indicates the constant balance of supply and demand other conditions being equal. As a result, a new economic quality of information is created. This feature is an indicator of the market as a self-regulated system. Monetized information quality is less popular than that of the Public Broadcasting Service, but this audience is able to make decisions. These very users keep the niche sectors which have more potential of technology development, including the content monetization ways. The third point of the study allows develop it in the discourse of media space liberalization. This cultural phenomenon may open opportunities for the development of social and economic relations architecture both locally and regionally.

Keywords: content monetization, state capitalism, media liberalization, media economy, information quality

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Authors: Juan F. Gutierrez, Jesus M. Quintero, Diego Sandoval

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An important feature of LED technology is the fast on-off commutation, which allows data transmission. Visible Light Communication (VLC) is a wireless method to transmit data with visible light. Modulation formats such as On-Off Keying (OOK) and Color Shift Keying (CSK) are used in VLC. Since CSK is based on three color bands uses red, green, and blue monochromatic LED (RGB-LED) to define a pattern of chromaticities. This type of CSK provides poor color quality in the illuminated area. This work presents the design and implementation of a VLC system using RGB-based CSK with 16, 8, and 4 color points, mixing with a steady baseline of a phosphor white-LED, to improve the color quality of the LED-Fixture. The experimental system was assessed in terms of the Color Rendering Index (CRI) and the Symbol Error Rate (SER). Good color quality performance of the LED-Fixture was obtained with an acceptable SER. The laboratory setup used to characterize and calibrate an LED-Fixture is described.

Keywords: VLC, indoor lighting, color quality, symbol error rate, color shift keying

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Ljerka Kratofil Krehula, Vanja Gilja, Andrea Husak, Sniježana Šuka, Zlata Hrnjak-Murgić

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Zinc oxide (ZnO) can be used as photocatalysts for water purification. However, one particular interest is given on the integration of inorganic ZnO nanoclusters with conducting polymers because the resulting nanocomposites may possess unique properties and enhanced photocatalytic activity in comparison to pure ZnO, using UV and also visible light. It is needed to explore the appropriate structure of polypyrrole that can induce activation of ZnO photocatalyst since the synthesis of organic/inorganic hybrid materials can result in a synergistic and complementary feature, increasing ZnO photocatalytic efficiency. In this paper several different composites of polypyrrole/zinc oxide (ZnO) were studied. Composite samples were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), cyclic voltammetry (CV) and scanning electron microscopy (SEM). The photocatalytic efficiency of prepared samples was studied as a decomposition of Reactive Red 45 (RR 45) dye, which was monitored by UV-Vis spectroscopy as a change in absorbance of characteristic wavelength at 542 nm. Results show good photocatalytic efficiency of all nanocomposite samples.

Keywords: photocatalysis, polypyrrole, wastewater, zinc oxide

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Authors: E. Arcos, E. Bautista, F. Méndez

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In this work, a scaling analysis of the liquefaction phenomena is presented. The characteristic scales are obtained by balancing term by term of the well-known partial dynamics governing equations, (U − P). From the above, the order of magnitude of the horizontal displacement is very smaller compared with the vertical displacement and therefore the governing equation is only a function of the dependent vertical variables. The U − P approximation is reduced and presented in its dimensionless version. This scaling analysis can be used to obtain analytical solutions of the liquefaction phenomena under the action of the water waves.

Keywords: approximation U-P, porous seabed, scaling analysis, water waves

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Authors: M. Nosik, I. Rymanova, N. Adamovich, S. Sevostyanihin, K. Ryzhov, Y. Kuimova, A. Kravtchenko, N. Sergeeva, A. Sobkin

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HIV and Tuberculosis (TB) infections each speed the other's progress. HIV-infection increases the risk of TB disease. At the same time, TB infection is associated with clinical progression of HIV-infection. HIV+TB co-infected patients are also at higher risk of acquiring new opportunistic infections. An important feature of disease progression and clinical outcome is the innate and acquired immune responses. HIV and TB, however, have a spectrum of dysfunctions of the immune response. As cytokines play a crucial role in the immunopathology of both infections, it is important to study immune interactions in patients with dual infection HIV+TB. Plasma levels of proinflammatory cytokines IL-2, IFN-γ and immunoregulating cytokines IL-4, IL-10 were evaluated in 75 patients with dual infection HIV+TB, 58 patients with HIV monoinfection and 50 patients with TB monoinfection who were previously naïve for HAART. The decreased levels of IL-2, IFN-γ, IL-4 and IL-10 were observed in patients with dual infection HIV+TB in comparison with patients who had only HIV or TB which means the profound suppression of Th1 and Th2 cytokine secretion. Thus, those cytokines could possibly serve as immunological markers of progression of HIV-infection in patients with TB.

Keywords: HIV, tuberculosis (TB), HIV associated with TB, Th1/ Th2 cytokine expression

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Authors: Khaled Harrar, Rachid Jennane

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The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an age-matched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.

Keywords: osteoporosis, fractal dimension, fractal signature, bone mineral density

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Authors: Jhu-Wei Ji, Fa-Shian Chang, Lih-Tyng Hwang, Chih-Feng Liu, Jeng-Nan Lee, Shun-Min Wang, Kai-Yi Cho

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This paper presents a tracked robot with blade arms powered to assist movement in difficult environments. As a result, the tracked robot is able to pass a ramp or climb stairs. The main feature is a pair of blade arms on both sides of the vehicle body working in collaboration with previously validated transformable track system. When the robot encounters an obstacle in a terrain, it enlists the blade arms with power to overcome the obstacle. In disaster areas, there usually will be terrains that are full of broken and complicated slopes, broken walls, rubbles, and ditches. Thereupon, a robot, which is instructed to pass through such disaster areas, needs to have a good off-road capability for such complicated terrains. The robot with crawling-assisting blade arms would overcome the obstacles along the terrains, and possibly become to be a rescue robot. A prototype has been developed and built; experiments were carried out to validate the enhanced crawling capability of the robot.

Keywords: tracked robot, rescue robot, blade arm, crawling ability, control system

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Authors: Ronak Khosravi, Mahmood Abbasi Layegh, Siamak Haghipour, Avin Esmaili

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In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function.

Keywords: coefficient features, relevance vector machines, spectral features, support vector machines, temporal features

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Hemalatha Rallapalli, K. Lal Kishore

Abstract:

In comparison to systems that are typically designed to provide capabilities over a narrow frequency range through hardware elements, the next generation cognitive radios are intended to implement a broader range of capabilities through efficient spectrum exploitation. This offers the user the promise of greater flexibility, seamless roaming possible on different networks, countries, frequencies, etc. It requires true paradigm shift i.e., liberalization over a wide band of spectrum as well as a growth path to more and greater capability. This work contributes towards the design and implementation of an open spectrum access (OSA) feature to unlicensed users thus offering a frequency agile radio platform that is capable of performing spectrum sensing over a wideband. Thus, an ultra-wideband (UWB) radio, which has the intelligence of spectrum sensing only, unlike the cognitive radio with complete intelligence, is named as a Smart Software Radio (SSR). The spectrum sensing mechanism is implemented based on energy detection. Simulation results show the accuracy and validity of this method.

Keywords: cognitive radio, energy detection, software radio, spectrum sensing

Procedia PDF Downloads 429

Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

Abstract:

Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: Graphviz representation, semantic relatedness, similarity measurement, WordNet similarity

Procedia PDF Downloads 239