Search results for: intelligent techniques

Authors: Hasan Hassoun, Jaafar Hallal, Denis Duhamel, Mohammad Hammoud, Ali Hage Diab

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This paper aims to prove the accuracy of an inexpensive smartphone camera as a non-contact vibration sensor to recover the vibration modes of a vibrating structure such as a cantilever beam. A video of a vibrating beam is filmed using a smartphone camera and then processed by the motion magnification technique. Based on this method, the first two natural frequencies and their associated mode shapes are estimated experimentally and compared to the analytical ones. Results show a relative error of less than 4% between the experimental and analytical approaches for the first two natural frequencies of the beam. Also, for the first two-mode shapes, a Modal Assurance Criterion (MAC) value of above 0.9 between the two approaches is obtained. This slight error between the different techniques ensures the viability of a cheap smartphone camera as a non-contact vibration sensor, particularly for structures vibrating at relatively low natural frequencies.

Keywords: modal analysis, motion magnification, smartphone camera, structural vibration, vibration modes

Procedia PDF Downloads 148

Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: Ojoniyi Oluwafeyekikunmi Okiki

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Notwithstanding advances in disturbing wound care and control, infections remain a main motive of mortality, morbidity, and financial disruption in tens of millions of wound sufferers around the sector. Animal models have become popular gear for analyzing a big selection of outside worrying wound infections and trying out new antimicrobial techniques. This evaluation covers experimental infections in animal models of surgical wounds, pores and skin abrasions, burns, lacerations, excisional wounds, and open fractures. Animal modes of external stressful wound infections stated via extraordinary investigators vary in animal species used, microorganism traces, the quantity of microorganisms carried out, the dimensions of the wounds, and, for burn infections, the period of time the heated object or liquid is in contact with the skin. As antibiotic resistance continues to grow, new antimicrobial procedures are urgently needed. Those have to be examined using popular protocols for infections in external stressful wounds in animal models.

Keywords: surgical wounds, animals, wound infections, burns, wound models, colony-forming gadgets, lacerated wounds

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Authors: S. Ramteke, K. S. Patel

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Aerosols are complex mixture of particulate matters (PM) inclusive of carbons, silica, elements, various salts, etc. Aerosols get deep into the human lungs and cause a broad range of health effects, in particular, respiratory and cardiovascular illnesses. They are one of the major culprits for the climate change. They are emitted by the high thermal processes i.e. vehicles, steel, sponge, cement, thermal power plants, etc. Raipur (22˚33'N to 21˚14'N and 82˚6'E) to 81˚38'E) is a growing industrial city in central India with population of two million. In this work, the distribution of inorganics (i.e. Cl⁻, NO³⁻, SO₄²⁻, NH₄⁺, Na⁺, K⁺, Mg²⁺, Ca²⁺, Al, Cr, Mn, Fe, Ni, Cu, Zn, and Pb) associated to the PM in the ambient air is described. The PM₁₀ in ambient air of Raipur city was collected for duration of one year (December 2014 - December 2015). The PM₁₀ was segregated into nine modes i.e. PM₁₀.₀₋₉.₀, PM₉.₀₋₅.₈, PM₅.₈₋₄.₇, PM₄.₇₋₃.₃, PM₃.₃₋₂.₁, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇, PM₀.₇₋₀.₄ and PM₀.₄ to know their emission sources and health hazards. The analysis of ions and metals was carried out by techniques i.e. ion chromatography and TXRF. The PM₁₀ concentration (n=48) was ranged from 100-450 µg/m³ with mean value of 73.57±20.82 µg/m³. The highest concentration of PM₄.₇₋₃.₃, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇ was observed in the commercial, residential and industrial area, respectively. The effect of meteorology i.e. temperature, humidity, wind speed and wind direction in the PM₁₀ and associated elemental concentration in the air is discussed.

Keywords: ambient aerosol, ions, metals, segregation

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Authors: Hilal Turkoglu Sasmazel, Ozan Ozkan, Seda Surucu

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Tissue engineering is the field of treating defects caused by injuries, trauma or acute/chronic diseases by using artificial scaffolds that mimic the extracellular matrix (ECM), the natural biological support for the tissues and cells within the body. The main aspects of a successful artificial scaffold are (i) large surface area in order to provide multiple anchorage points for cells to attach, (ii) suitable porosity in order to achieve 3 dimensional growth of the cells within the scaffold as well as proper transport of nutrition, biosignals and waste and (iii) physical, chemical and biological compatibility of the material in order to obtain viability throughout the healing process. By hybrid scaffolds where two or more different materials were combined with advanced fabrication techniques into complex structures, it is possible to combine the advantages of individual materials into one single structure while eliminating the disadvantages of each. Adding this to the complex structure provided by advanced fabrication techniques enables obtaining the desired aspects of a successful artificial tissue scaffold. In this study, fibroblast compatibility of poly(ε-caprolactone) (PCL)/chitosan core-shell electrospun hybrid scaffolds with proper mechanical, chemical and physical properties successfully developed in our previous study was investigated. Standard 7-day cell culture was carried out with L929 fibroblast cell line. The viability of the cells cultured with the scaffolds was monitored with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) viability assay for every 48 h starting with 24 h after the initial seeding. In this assay, blank commercial tissue culture polystyrene (TCPS) Petri dishes, single electrospun PCL and single electrospun chitosan mats were used as control in order to compare and contrast the performance of the hybrid scaffolds. The adhesion, proliferation, spread and growth of the cells on/within the scaffolds were observed visually on the 3rd and the 7th days of the culture period with confocal laser scanning microscopy (CSLM) and scanning electron microscopy (SEM). The viability assay showed that the hybrid scaffolds caused no toxicity for fibroblast cells and provided a steady increase in cell viability, effectively doubling the cell density for every 48 h for the course of 7 days, as compared to TCPS, single electrospun PCL or chitosan mats. The cell viability on the hybrid scaffold was ~2 fold better compared to TCPS because of its 3D ECM-like structure compared to 2D flat surface of commercially cell compatible TCPS, and the performance was ~2 fold and ~10 fold better compared to single PCL and single chitosan mats, respectively, even though both fabricated similarly with electrospinning as non-woven fibrous structures, because single PCL and chitosan mats were either too hydrophobic or too hydrophilic to maintain cell attachment points. The viability results were verified with visual images obtained with CSLM and SEM, in which cells found to achieve characteristic spindle-like fibroblast shape and spread on the surface as well within the pores successfully at high densities.

Keywords: chitosan, core-shell, fibroblast, electrospinning, PCL

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Authors: Bissonnette Jean-François, Dossa Fabrice

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The project focuses on analyzing the spatial and temporal evolution of mangrove forest ecosystems near the city of Douala, Cameroon, in response to increasing human and environmental pressures. The selected study area, located in the Wouri River estuary, has a unique combination of economic importance, and ecological prominence. The study included valuable insights by conducting semi-structured interviews with resource operators and local officials. The thorough analysis of socio-economic data, farmer surveys, and satellite-derived information was carried out utilizing quantitative approaches in Excel and SPSS. Simultaneously, qualitative data was subjected to rigorous classification and correlation with other sources. The use of ArcGIS and CorelDraw facilitated the visual representation of the gradual changes seen in various land cover classifications. The research reveals complex processes that characterize mangrove ecosystems on Manoka and Cape Cameroon Islands. The lack of regulations in urbanization and the continuous growth of infrastructure have led to a significant increase in land conversion, causing negative impacts on natural landscapes and forests. The repeated instances of flooding and coastal erosion have further shaped landscape alterations, fostering the proliferation of water and mudflat areas. The unregulated use of mangrove resources is a significant factor in the degradation of these ecosystems. Activities including the use of wood for smoking and fishing, together with the coastal pollution resulting from the absence of waste collection, have had a significant influence. In addition, forest operators contribute to the degradation of vegetation, hence exacerbating the harmful impact of invasive species on the ecosystem. Strategic interventions are necessary to guarantee the sustainable management of these ecosystems. The proposals include advocating for sustainable wood exploitation techniques, using appropriate techniques, along with regeneration, and enforcing rules to prevent wood overexploitation. By implementing these measures, the ecological balance can be preserved, safeguarding the long-term viability of these precious ecosystems. On a conceptual level, this paper uses the framework developed by Elinor Ostrom and her colleagues to investigate the consequences of open access resources, where local actors have not been able to enforce measures to prevent overexploitation of mangrove wood resources. Governmental authorities have demonstrated limited capacity to enforce sustainable management of wood resources and have not been able to establish effective relationships with local fishing communities and with communities involved in the purchase of wood. As a result, wood resources in the mangrove areas remain largely accessible, while authorities do not monitor wood volumes extracted nor methods of exploitation. There have only been limited and punctual attempts at forest restoration with no significant consequence on mangrove forests dynamics.

Keywords: Mangroves, forest management, governance, open access resources, Cameroon

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Authors: S. B. Bansode, V. G. Wagh, R. S. Kapadnis, S. S. Kale, M. Pathan Habib

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Indium sulfide films have been deposited using chemical bath deposition onto glass and indium tin oxide coated glass substrates. The influences of different deposition parameters viz. substrate and pH have been studied. The films were characterized by different techniques with respect to their crystal structure, surface morphology and compositional property by means of X-ray diffraction, scanning electron microscopy, Energy dispersive spectroscopy and optical absorption. X-ray diffraction studies revealed that amorphous nature of the films. The scanning electron microscopy of as deposited indium sulfide film on ITO coated glass substrate shows random orientation of grains where as those on glass substrates show dumbbell shape. Optical absorption study revealed that band gap varies from 2.29 to 2.79 eV for the deposited film.

Keywords: chemical bath deposition, optical properties, structural property, Indium sulfide

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Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

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Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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Authors: Xiaohong Yang, Haitao Fu, Xizhong An, Aibing Yu

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Silver@titanium dioxide (Ag@TiO2) core-shell nanostructures and Ag surface doped TiO2 particles (TiO2@Ag) have been designed and synthesized by sol-gel and hydrothermal methods under mild conditions. These two types of Ag/TiO2 nanocomposites were characterized in terms of their properties by various techniques such as transmission electron microscope (TEM), X-ray diffraction (XRD), Brunauer Emmett Teller (BET) and ultra violet-visible absorption spectroscopy (UV-Vis). Specifically, the photocatalystic performance and antibacterial behavior of such nanocomposites have been investigated and compared. It was found that The Ag@TiO2 core-shell nanostructures exhibit superior photocatalytic property to the Ag surface doped TiO2 particles under the reported conditions. While with UV pre-irradiation, the Ag@TiO2 core-shell composites exhibit better bactericidal performance. This is probably because the Ag cores tend to facilitate charge separation for TiO2, producing greater hydroxyl radicals on the surface of the TiO2 particles. These findings would be useful for the design and synthesis of Ag/TiO2 nanocomposites with desirable photocatalystic and antimicrobial activity for environmental applications.

Keywords: Ag@TiO2 core-shell nanoparticles, Ag surface doped TiO2 nanoparticles, photocatalysis, antibacterial

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Authors: Hasan A Al-Asadi, Ali Samir, Afrah Turki Awad, Ali Basem

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Integrating the phase change material (PCM) with photovoltaic (PV) panels is one of the effective techniques to minimize the PV panel temperature and increase their electric output. In order to investigate the impact of the PCM on the electric output of the PV panels for a whole year, a lumped-distributed parameter model for the PV-PCM module has been developed. This development has considered the impact of the PCM density variation between the solid phase and liquid phase. This contribution will increase the assessment accuracy of the electric output of the PV-PCM module. The second contribution is to assess the impact of the expanded composite graphite-PCM on the PV electric output in Milan for a whole year. The novel one-dimensional model has been solved using MATLAB software. The results of this model have been validated against literature experiment work. The weather and the solar radiation data have been collected. The impact of expanded graphite-PCM on the electric output of the PV panel for a whole year has been investigated. The results indicate this impact has an enhancement rate of 2.39% for the electric output of the PV panel in Milan for a whole year.

Keywords: PV panel efficiency, PCM, numerical model, solar energy

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Authors: Sushant Singh, Anurag Jain, Seema Sabharwal

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Cloud computing is advancing with a rapid speed. Already, it has been adopted by a huge set of users. Easy to use and anywhere access like potential of cloud computing has made it more attractive relative to other technologies. This has resulted in reduction of deployment cost on user side. It has also allowed the big companies to sell their infrastructure to recover the installation cost for the organization. Roots of cloud computing have extended from Grid computing. Along with the inherited characteristics of its predecessor technologies it has also adopted the loopholes present in those technologies. Some of the loopholes are identified and corrected recently, but still some are yet to be rectified. Two major areas where still scope of improvement exists are security and performance. The proposed work is devoted to performance enhancement for the user of the existing cloud system by improving the basic throttled mapping approach between task and resources. The improved procedure has been tested using the cloud analyst simulator. The results are compared with the original and it has been found that proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, load balancing, throttled

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Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

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What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

Procedia PDF Downloads 348

Authors: Akram Hashemi

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This study provided an empirical evidence for learners of elementary level of language proficiency to investigate the potential role of contextualization in vocabulary learning. Prior to the main study, pilot study was performed to determine the reliability and validity of the researcher-made pretest and posttest. After manifesting the homogeneity of the participants, the participants (n = 90) were randomly assigned into three equal groups, i.e., two experimental groups and a control group. They were pretested by a vocabulary test, in order to test participants' pre-knowledge of vocabulary. Then, vocabulary instruction was provided through three methods of visual instruction, the use of context and the use of conventional techniques. At the end of the study, all participants took the same posttest in order to assess their vocabulary gain. The results of independent sample t-test indicated that there is a significant difference between learning vocabulary visually and learning vocabulary contextually. The results of paired sample t-test showed that different teaching strategies have significantly different impacts on learners’ vocabulary gains. Also, the contextual strategy was significantly more effective than visual strategy in improving students’ performance in vocabulary test.

Keywords: vocabulary instruction, explicit instruction, implicit instruction, strategy

Procedia PDF Downloads 335

Authors: Khedidja Benouis

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Environmental issues in the food industry are related to the water because it consumes water and release large volumes of wastewater. The treatment of such discharges techniques can be adapted to different situations encountered. For dairy effluents, it is necessary and very effective to use a treatment that eliminates much of the pollutant load,thus, to drastically reduce the organic loading rate. This study aims to evaluate the Efficiency and limitations of physicochemical treatment by coagulation - flocculation of liquid effluent from this type of food industry in Algeria, to give an example of the type and the degree of pollution generated by this sector and in order to reduce pollution and minimize its environmental issues. Coagulation - flocculation-sedimentation was carried out using lime without addition of additive (flocculant), the processing efficiency is indicated by the concentration of pollutants in treated water. The results show that treatment is not sufficient to remove organic pollution, but it has significantly reduced the Total suspended solids (TSS), nitrate (NO3-N) and phosphate (PO4-P).

Keywords: Algeria, coagulation-flocculation, dairy effluent, treatment

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Authors: Sonali Mohite

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Severe changes to Organizational Sustainability (OS) have been brought about by the COVID-19 pandemic. This situation forces organizations to tackle the competencies required to augment Employee Resilience (ER) and make profitable growth. This study explores how employee resilience contributes to both individual and organizational success in the wake of the COVID-19 pandemic. We suggest that employees who possess strong coping mechanisms and adaptability are better equipped to handle ongoing disruptions, resulting in improved individual performance metrics like productivity, engagement, and innovative thinking. Hence, exploring the efficiency of ER in improving EP and OS in post-pandemic (PP) is the aim of this research. By utilizing convenience sampling techniques, a total of 422 employees have been collected from numerous organizations. After that, the study’s hypothesis is analysed by using Structural Equation Modelling (SEM). As per the study’s findings, the ER factors of “Job Satisfaction (JS)”, “Self-Efficacy (SE)”, “Supervisors’ Support (SS)”, and “Facilitating Conditions (FC)” have positive and significant associations with organizational efficiency. Furthermore, the study’s findings also exhibited that there is the most important relation between SE and EOP.

Keywords: employee resilience, employee performance, organizational performance, sustainability, post-pandemic

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Authors: Bharat P. Modi, Jayesh M. Patel

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Mobile Internet is acting as a major source of data. As the number of web pages continues to grow the Mobile web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need, a special term called Mobile Web mining was coined. Mobile Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Mobile Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, a number of bytes transferred time-stamp etc. A variety of Log Analyzer tools exists which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Mobile Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

Keywords: mobile web access logs, web usage mining, web server, log analyzer

Procedia PDF Downloads 362

Authors: Adriana Souza M. Batista, Cláubia Pereira, Luiz O. Faria

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The irradiation of polymeric materials has received much attention because it can produce diverse changes in chemical structure and physical properties. Thus, studying the chemical and structural changes of polymers is important in practice to achieve optimal conditions for the modification of polymers. The effect of gamma irradiation on the crystalline structure of poly(vinylidene fluoride) (PVDF) has been investigated using differential scanning calorimetry (DSC) and X-ray diffraction techniques (XRD). Gamma irradiation was carried out in atmosphere air with doses between 100 kGy at 3,000 kGy with a Co-60 source. In the melting thermogram of the samples irradiated can be seen a bimodal melting endotherm is detected with two melting temperature. The lower melting temperature is attributed to melting of crystals originally present and the higher melting peak due to melting of crystals reorganized upon heat treatment. These results are consistent with those obtained by XRD technique showing increasing crystallinity with increasing irradiation dose, although the melting latent heat is decreasing.

Keywords: differential scanning calorimetry, gamma irradiation, PVDF, X-ray diffraction technique

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Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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Authors: Bekhedda Kheira

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Rare earth-doped luminescent materials (Ce, Eu, Yb, Tb, etc.) are now widely used in flat-screen displays, fluorescent lamps, and photovoltaic solar cells. They exhibit several fine emission bands in a spectral range from near UV to infrared when added to inorganic materials. This study chose cerium oxide (CeO2) because of its exceptional intrinsic properties, energy levels, and ease of implementation of doped layer synthesis. In this study, thin films were obtained by the evaporation deposition technique of cerium oxide (CeO2) on silicon Nitride (SiNx) layers and then annealing under nitrogen N2. The characterization of these films was carried out by different techniques, scanning electron microscopy (SEM) to visualize morphological properties and (EDS) was used to determine the elemental composition of individual dots, optical analysis characterization of thin films was studied by a spectrophotometer in reflectance mode to determine different energies gap of the nanostructured layers and to adjust these values for the photovoltaic application.

Keywords: thin films, photovoltaic, rare earth, evaporation

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Mohsin Talib Mohammed, Zahid A. Khan, Arshad N. Siddiquee

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The wide use of titanium (Ti) materials in medicine gives impetus to a search for development new techniques with elevated properties such as strength, corrosion resistance and Young's modulus close to that of bone tissue. This article presents the most recent state of the art on the use of equal channel angular pressing (ECAP) technique in evolving mechanical characteristics of the ultrafine-grained bio-grade Ti materials. Over past few decades, research activities in this area have grown enormously and have produced interesting results, including achieving the combination of conflicting properties that are desirable for biomedical applications by severe plastic deformation (SPD) processing. A comprehensive review of the most recent work in this area is systematically presented. The challenges in processing ultrafine-grained Ti materials are identified and discussed. An overview of the biomedical Ti alloys processed with ECAP technique is given in this review, along with a summary of their effect on the important mechanical properties that can be achieved by SPD processing. The paper also offers insights in the mechanisms underlying SPD.

Keywords: mechanical properties, ECAP, titanium, biomedical applications

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Authors: Rubén Manrique, Delio Balcázar, José Parrado, Sebastián Rodríguez

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Hand in hand with the evolution of technology, education systems have moved to virtual environments to provide increased coverage and facilitate the access to education. However, measuring student performance in virtual environments presents significant challenges to ensure students are acquiring the expected skills. In this study, the confidence and performance of engineering students in virtual environments is analyzed through different evaluation strategies. The effect of the assessment strategy in student confidence is identified using educational data mining techniques. Four assessment strategies were used. First, a conventional multiple choice test; second, a multiple choice test with feedback; third, a multiple choice test with a second chance; and fourth; a multiple choice test with feedback and second chance. Our results show that applying testing with online feedback strategies can influence positively student confidence.

Keywords: assessment strategies, educational data mining, student performance, student confidence

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Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud

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The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.

Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow

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Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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Authors: Mohamedou El Boukhary, Farba Bouyagui Tamboura, A. Hamady Barry, T. Moussa Seck, Mohamed L. Gaye

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Nowadays, low-schiff acyl-hydrazone ligands are highly sought after due to their wide applications in various fields of biology, coordination chemistry, and catalysis. They are studied for their antioxidant, antibacterial and antiviral properties. The complexes of transition metals and the lanthanide they derive are well known for their magnetic, optical, and catalytic properties. In this work, we present the synthesis of an acyl-hydrazone (H2L) schiff base and their 3d transition complexes. The ligand (H2L) is characterized by IR, NMR (1H; 13C) spectroscopy. The complexes are characterized by different physic-chemical techniques such as IR, UV-visible, conductivity, measurement of magnetic susceptibility. The study of XRD allowed us to elucidate the crystalline structure of the manganese (Mn) complex. The asymmetric unit of the complex is composed of two molecules of the ligand, one manganese (II) ion, and two coordinate chloride ions; the environment around Mn is described as a pentagonal base bipyramid. In the crystal lattice, the asymmetric unit is bound by hydrogen bonds.

Keywords: synthene, acyl-hydrazone, 3D transition metal complex, application

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Suzan Anwar, Utkarsh Goyal

Abstract:

Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

Procedia PDF Downloads 138

Authors: Elham Rouhollahi, Soheil Zorofchian Moghadamtousi, Salma Baig, Mahmood Ameen Abdulla, Zahurin Mohamed

Abstract:

This study was designed to assess cutaneous wound healing potential of hexane extract of Curcuma purpurascens rhizomes (HECP). Twenty-four rats were divided into 4 groups: 1. Negative, 2. Low dose, 3. High dose and 4. Treatment, with 6 rats in each group. Full-thickness incisions with a diameter of 2 cm were made on the back of each rat. Rats were topically treated two times a day for 15 days. Group 1-4 were treated with sterile distilled water, 5% and 10% of extract and intrasite gel, respectively. Masson's trichrome and hematoxylin staining techniques are employed for histological analysis revealed strong wound healing potential closer to that of conventional drug intrasite gel. HECP significantly decreased wound area and an increase in hydroxyproline, cellular proliferation, the number of blood vessels and the level of collagen synthesis was observed. Thus, it could be concluded that HECP possesses strong wound healing potential.

Keywords: Curcuma purpurascens, wound healing, histopathology, hematoxylin staining

Procedia PDF Downloads 438

Authors: Willy Mbenza, Sho Kenjiro

Abstract:

Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

Procedia PDF Downloads 90