Search results for: information value method

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

Procedia PDF Downloads 156

Authors: Faiza Hussain, Usman Qamar

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Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

Procedia PDF Downloads 308

Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

Procedia PDF Downloads 107

Authors: Musa Auwal Mamman, S. G. Isa

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This study was carried out in order to investigate the effectiveness of GeoGebra software in teaching and learning of linear and quadratic equations amongst senior secondary school students in Fagge Local Government Area, Kano State–Nigeria. Five research items were raised in objectives, research questions and hypotheses respectively. A random sampling method was used in selecting 398 students from a population of 2098 of SS2 students. The experimental group was taught using the GeoGebra software while the control group was taught using the conventional teaching method. The instrument used for the study was the mathematics performance test (MPT) which was administered at the beginning and at the end of the study. The results of the study revealed that students taught with GeoGebra software (experimental group) performed better than students taught with traditional teaching method. The t- test was used to analyze the data obtained from the study.

Keywords: GeoGebra Software, mathematics performance, random sampling, mathematics teaching

Procedia PDF Downloads 247

Authors: Shidvash Vakilipour, Masoud Mohammadi, Rouzbeh Riazi, Scott Ormiston, Kimia Amiri, Sahar Barati

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An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.

Keywords: cell-centered finite volume method, coupled solver, exponential differencing scheme (EDS), physical influence scheme (PIS), pressure weighted interpolation method (PWIM), skew upwind differencing scheme (SUDS)

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Authors: Gabriela Prins, Quinette Louw, Dawn Ernstzen

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Background: Access to rehabilitation services is a major challenge globally, especially in low-and-middle income countries (LMICs) where resources and infrastructure are extremely limited. Telerehabilitation (TR) has emerged in recent decades as a highly promising method to dramatically expand accessibility to rehabilitation services globally. TR provides rehabilitation care remotely using communication technologies such as video conferencing, smartphones, and internet-connected devices. This boosts accessibility to underprivileged regions and allows for greater flexibility for patients. Despite this, TR is hindered by several factors, including limited technological resources, high costs, lack of digital access, and the unavailability of healthcare systems, which are major barriers to widespread adoption among LMIC patients. These barriers have collectively hindered the potential implementation and adoption of TR services in LMICs healthcare settings. Adoption of TR will also require the buy-in of end users and limited information is known on the perspectives of the SA population. Aim: The study aimed to understand patients' perspectives regarding the use of digital technology as part of their OA rehabilitation at a public community healthcare centre in the Cape Metropole Area. Methods: A qualitative descriptive study design was used on 10 OA patients from a public community rehabilitation centre in South Africa. Data collection included semi-structured interviews and patient-reported outcome measures (PSFS, ASES-8, and EuroQol EQ-5D-5L) on functioning and quality of life. Transcribed interview data were coded in Atlas.ti. 22.2 and analyzed using thematic analysis. The results were narratively documented. Results: Four themes arose from the interviews. The themes were Telerehabilitation awareness (Use of Digital Technology Information Sources and Prior Experience with Technology /TR), Telerehabilitation Benefits (Access to healthcare providers, Access to educational information, Convenience, Time and Resource Efficiency and Facilitating Family Involvement), Telerehabilitation Implementation Considerations (Openness towards TR Implementation, Learning about TR and Technology, Therapeutic relationship, and Privacy) and Future use of Telerehabilitation (Personal Preference and TR for the next generation). The ten participants demonstrated limited awareness and exposure to TR, as well as minimal digital literacy and skills. Skepticism was shown when comparing the effectiveness of TR to in-person rehabilitation and valued physical interactions with health professionals. However, some recognized potential benefits of TR for accessibility, convenience, family involvement and improving community health in the long term. Willingness existed to try TR with sufficient training. Conclusion: With targeted efforts addressing identified barriers around awareness, technological literacy, clinician readiness and resource availability, perspectives on TR may shift positively from uncertainty towards endorsement of this expanding approach for simpler rehabilitation access in LMICs.

Keywords: digital technology, osteoarthritis, primary health care, telerehabilitation

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Authors: Ghada Ben Hamad, Zohir Younsi, Fabien Salaun, Hassane Naji, Noureddine Lebaz

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The graphene oxide (GO) material has attracted much attention for solar energy applications. This paper reports the synthesis and characterization of partially oxidized graphite oxide (GTO). GTO was obtained by modified Hummers method, which is based on the chemical oxidation of natural graphite. Several samples were prepared with different oxidation degree by an adjustment of the oxidizing agent’s amount. The effect of the oxidation degree on the chemical structure and on the morphology of GTO was determined by using Fourier transform infrared (FT-IR) spectroscopy, Energy Dispersive X-ray Spectroscopy (EDS), and scanning electronic microscope (SEM). The thermal stability of GTO was evaluated by using thermogravimetric analyzer (TGA) in Nitrogen atmosphere. The results indicate high degree oxidation of graphite oxide for each sample, proving that the process is efficient. The GTO synthesized by modified Hummers method shows promising characteristics. Graphene oxide (GO) obtained by exfoliation of GTO are recognized as a good candidate for thermal energy storage, and it will be used as solid shell material in the encapsulation of phase change materials (PCM).

Keywords: modified hummers method, graphite oxide, oxidation degree, solar energy storage

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Authors: Mourad Hrizi

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In this paper, we study the inverse problem of reconstructing an interior interface D appearing in the elliptic partial differential equation: Δu+χ(D)u=0 from the knowledge of the boundary measurements. This problem arises from a semiconductor transistor model. We propose a new shape reconstruction procedure that is based on the Kohn-Vogelius formulation and the topological sensitivity method. The inverse problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a function. The unknown subdomain D is reconstructed using a level-set curve of the topological gradient. Finally, we give several examples to show the viability of our proposed method.

Keywords: inverse problem, topological optimization, topological gradient, Kohn-Vogelius formulation

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Emad A. Mohammed

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The concept of hydraulic flow units (HFU) has been used for decades in the petroleum industry to improve the prediction of permeability. This concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir rock quality index (RQI). Both indices are based on reservoir porosity and permeability of core samples. It is assumed that core samples with similar FZI values belong to the same HFU. Thus, after dividing the porosity-permeability data based on the HFU, transformations can be done in order to estimate the permeability from the porosity. The conventional practice is to use the power law transformation using conventional HFU where percentage of error is considerably high. In this paper, neural network technique is employed as a soft computing transformation method to predict permeability instead of power law method to avoid higher percentage of error. This technique is based on HFU identification where Amaefule et al. (1993) method is utilized. In this regard, Kozeny and Carman (K–C) model, and modified K–C model by Hasan and Hossain (2011) are employed. A comparison is made between the two transformation techniques for the two porosity-permeability models. Results show that the modified K-C model helps in getting better results with lower percentage of error in predicting permeability. The results also show that the use of artificial intelligence techniques give more accurate prediction than power law method. This study was conducted on a heterogeneous complex carbonate reservoir in Oman. Data were collected from seven wells to obtain the permeability correlations for the whole field. The findings of this study will help in getting better estimation of permeability of a complex reservoir.

Keywords: permeability, hydraulic flow units, artificial intelligence, correlation

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Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

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Authors: Mbida Mohamed, Ezzati Abdellah

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A strong challenge in the wireless sensor networks (WSN) is to save the energy and have a long life time in the network without having a high rate of loss information. However, topology control (TC) protocols are designed in a way that the network is divided and having a standard system of exchange packets between nodes. In this article, we will propose a clustering based and centralized routing table protocol of TC (CBCRT) which delegates a leader node that will encapsulate a single routing table in every cluster nodes. Hence, if a node wants to send packets to the sink, it requests the information's routing table of the current cluster from the node leader in order to root the packet.

Keywords: mobile wireless sensor networks, routing, topology of control, protocols

Procedia PDF Downloads 274

Authors: Motoki Seguchi, Fumiko Harada, Hiromitsu Shimakawa

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There have been many local companies in countryside that carefully produce and sell products, which include crafts and foods produced with traditional methods. These companies are likely to use commercials to advertise their products. However, it is difficult for companies to judge whether the commercials they create are having an impact on consumers. Therefore, to create effective commercials, this study researches what kind of gimmicks in commercials affect what kind of consumers. This study proposes a method for extracting psychological change points from the physiological characteristics of consumers while they are watching commercials and estimating the gimmicks in the commercial that affect consumer engagement. In this method, change point detection is applied to pupil size for estimating gimmicks that affect consumers’ emotional engagement, and to EDA for estimating gimmicks that affect cognitive engagement. A questionnaire is also used to estimate the commercials that influence behavioral engagement. As a result of estimating the gimmicks that influence consumer engagement using this method, it was found that there are some common features among the gimmicks. To influence cognitive engagement, it was found that it was useful to include flashback scenes, messages to be appealed to, the company’s name, and the company’s logos as gimmicks. It was also found that flashback scenes and story climaxes were useful in influencing emotional engagement. Furthermore, it was found that the use of storytelling commercials may or may not be useful, depending on which consumers are desired to take which behaviors. It also estimated the gimmicks that influence consumers for each target and found that the useful gimmicks are slightly different for students and working adults. By using this method, it can understand which gimmicks in the commercial affect which engagement of the consumers. Therefore, the results of this study can be used as a reference for the gimmicks that should be included in commercials when companies create their commercials in the future.

Keywords: change point detection, estimating engagement, physiological characteristics, psychological changes, watching commercials

Procedia PDF Downloads 186

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

Procedia PDF Downloads 93

Authors: Thidarat Duangyod, Chanida Palanuvej, Nijsiri Ruangrungsi

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Pentace burmanica Kurz., belonging to the Malvaceae family, is commonly used for anti-diarrhea in Thai traditional medicine. A method for quantification of (+)-catechin and (-)-epicatechin in P. burmanica stem bark from 12 different Thailand markets by reverse-phase high performance liquid chromatography (HPLC) was investigated and validated. The analysis was performed by a Shimadzu DGU-20A3 HPLC equipped with a Shimadzu SPD-M20A photo diode array detector. The separation was accomplished with an Inersil ODS-3 column (5 µm x 4.6 x 250 mm) using 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B) as mobile phase at the flow rate of 1 ml/min. The isocratic was set at 20% B for 15 min and the column temperature was maintained at 40 ºC. The detection was at the wavelength of 280 nm. Both (+)-catechin and (-)-epicatechin existed in the ethanolic extract of P. burmanica stem bark. The content of (-)-epicatechin was found as 59.74 ± 1.69 µg/mg of crude extract. In contrast, the quantitation of (+)-catechin content was omitted because of its small amount. The method was linear over a range of 5-200 µg/ml with good coefficients (r2 > 0.99) for (+)-catechin and (-)-epicatechin. Limit of detection values were found to be 4.80 µg/ml for (+)-catechin and 5.14 µg/ml for (-)-epicatechin. Limit of quantitation of (+)-catechin and (-)-epicatechin were of 14.54 µg/ml and 15.57 µg/ml respectively. Good repeatability and intermediate precision (%RSD < 3) were found in this study. The average recoveries of both (+)-catechin and (-)-epicatechin were obtained with good recovery in the range of 91.11 – 97.02% and 88.53 – 93.78%, respectively, with the %RSD less than 2. The peak purity indices of catechins were more than 0.99. The results suggested that HPLC method proved to be precise and accurate and the method can be conveniently used for (+)-catechin and (-)-epicatechin determination in ethanolic extract of P. burmanica stem bark. Moreover, the stem bark of P. burmanica was found to be a rich source of (-)-epicatechin.

Keywords: pentace burmanica, (+)-catechin, (-)-epicatechin, high performance liquid chromatography

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Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

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Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

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Authors: Anton V. Bourdine, Vladimir A. Burdin, Oleg R. Delmukhametov

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This work presents a fast and simple method for the design of large core silica optical fibers with differential mode delay (DMD) management. Some results are reported concerned with refractive index profile optimization for 42 µm core 16-LP-mode optical fiber for next-generation optical networks. Here special refractive index profile form provides total DMD reducing over all mode staff under desired enhanced mode effective area. Method for the simulation of 'real manufactured' few-mode optical fiber (FMF) core geometry differing from the desired optimized structure by core non-symmetrical ellipticity and refractive index profile deviation including local fluctuations is proposed. Results of the following analysis of optimized FMF with inserted geometry distortions performed by earlier on developed modification of rigorous mixed finite-element method showed strong DMD degradation that requires additional higher-order mode management. In addition, this work also presents a method for design mode division multiplexer channel precision spatial positioning scheme at FMF core end that provides one of the potentiality solutions of described DMD degradation problem concerned with 'distorted' core geometry due to features of optical fiber manufacturing techniques.

Keywords: differential mode delay, few-mode optical fibers, nonlinear Shannon limit, optical fiber non-circularity, ‘real manufactured’ optical fiber core geometry simulation, refractive index profile optimization

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Authors: Yuliya Leonidovna Kiva-Khamzina

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The legal nature of the contract for educational services causes a lot of controversies. In particular, it raises the question about industry sector relationships, which require making a contract for educational services. The article describes the different types of contracts classifications for services provision from the perspective of civil law, deals with the specifics of the contract on rendering educational services; the author makes the conclusion that the contract for the provision of educational services is a complex institution that includes elements of the civil and administrative law. The following methods were used to conduct the study: dialectical method of cognition, the historical method, systemic analysis, classification.

Keywords: administrative aspect, civil aspect, educational service, industry, legal nature, services provision

Procedia PDF Downloads 324

Authors: Wenxue Xu

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Fluid resistance damper is an important damping element to attenuate vehicle vibration. It converts vibration energy into thermal energy dissipation through oil throttling. It is a typical fluid-solid-heat coupling problem. A complete three-dimensional flow-structure-thermal coupling dynamics simulation model of a gas-filled fluid-resistance damper was established. The flow-condition-based interpolation (FCBI) method and direct coupling calculation method, the unit's FCBI-C fluid numerical analysis method and iterative coupling calculation method are used to achieve the damper dynamic response of the piston rod under sinusoidal excitation; the air chamber inflation pressure, spring compression characteristics, constant flow passage cross-sectional area and oil parameters, etc. The system parameters, excitation frequency, and amplitude and other excitation parameters are analyzed and compared in detail for the effects of differential pressure characteristics, velocity characteristics, flow characteristics and dynamic response of valve opening, floating piston response and piston rod output force characteristics. Experiments were carried out on some simulation analysis conditions. The results show that the node-based FCBI (flow-condition-based interpolation) fluid numerical analysis method and direct coupling calculation method can better guarantee the conservation of flow field calculation, and the calculation step is larger, but the memory is also larger; if the chamber inflation pressure is too low, the damper will become cavitation. The inflation pressure will cause the speed characteristic hysteresis to increase, and the sealing requirements are too strict. The spring compression characteristics have a great influence on the damping characteristics of the damper, and reasonable damping characteristic needs to properly design the spring compression characteristics; the larger the cross-sectional area of the constant flow channel, the smaller the maximum output force, but the more stable when the valve plate is opening.

Keywords: damper, fluid-structure-thermal coupling, heat generation, heat transfer

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Authors: Shu Tao

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Based on a global fuel consumption data product (PKU-FUEL-2007) compiled recently and a series of databases for emission factors of various sources, global emission inventories of a number of greenhouse gases and air pollutants, including CO2, CO, SO2, NOx, primary particulate matter (total, PM 10, and PM 2.5), black carbon, organic carbon, mercury, volatile organic carbons, and polycyclic aromatic hydrocarbons, from combustion sources have been developed. The inventories feather high spatial and sectorial resolutions. The spatial resolution of the inventories are 0.1 by 0.1 degree, based on a sub-national disaggregation approach to reduce spatial bias due to uneven distribution of per person fuel consumption within countries. The finely resolved inventories provide critical information for chemical transport modeling and exposure modeling. Emissions from more than 60 sources in energy, industry, agriculture, residential, transportation, and wildfire sectors were quantified in this study. With the detailed sectorial information, the inventories become an important tool for policy makers. For residential sector, a set of models were developed to simulate temporal variation of fuel consumption, consequently pollutant emissions. The models can be used to characterize seasonal as well as inter-annual variations in the emissions in history and to predict future changes. The models can even be used to quantify net change of fuel consumption and pollutant emissions due to climate change. The inventories has been used for model ambient air quality, population exposure, and even health effects. A few examples of the applications are discussed.

Keywords: air pollutants, combustion, emission inventory, sectorial information

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Authors: S. Boukais, A. Nekmouche, N. Khelil, A. Kezmane

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The first intent of this study is to develop a finite element model that can predict correctly the behavior of the reinforced concrete column. Second aim is to use the finite element model to investigate and evaluate the effect of the strengthening method by jacketing of the reinforced concrete column, by considering different interface contact between the old and the new concrete. Four models were evaluated, one by considering perfect contact, the other three models by using friction coefficient of 0.1, 0.3 and 0.5. The simulation was carried out by using Abaqus software. The obtained results show that the jacketing reinforcement led to significant increase of the global performance of the behavior of the simulated reinforced concrete column.

Keywords: strengthening, jacketing, rienforced concrete column, Abaqus, simulation

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Authors: Abdul Ghani Rajput

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Although monitoring and evaluation concept adopted by Technical Vocational Education and Training (TVET) organization to track the progress over the continuous interval of time based on planned interventions and subsequently, evaluating it for the impact, quality assurance and sustainability. In digital world, TVET providers are giving preference to have real time information to do monitoring of training activities. Identifying the benefits and challenges of digitized monitoring & evaluation real time information system has not been sufficiently tackled in this date. This research paper looks at the impact of digitized M&E in TVET sector by analyzing two case studies and describe the benefits and challenges of using digitized M&E system. Finally, digitized M&E have been identified as carriers for high potential of TVET sector.

Keywords: digitized M&E, innovation, quality assurance, TVET

Procedia PDF Downloads 230

Authors: I. Wiemann, N. Weiß, E. Schlücker, M. Wensing, A. Kölpin

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Chemical storage of hydrogen by liquid organic hydrogen carriers (LOHC) is a very promising alternative to compression or cryogenics. These carriers have high energy density and allow at the same time efficient and safe storage of hydrogen under ambient conditions and without leakage losses. Another benefit of LOHC is the possibility to transport it using already available infrastructure for transport of fossil fuels. Efficient use of LOHC is related to a precise process control, which requires a number of sensors in order to measure all relevant process parameters, for example, to measure the level of hydrogen loading of the carrier. The degree of loading is relevant for the energy content of the storage carrier and represents simultaneously the modification in chemical structure of the carrier molecules. This variation can be detected in different physical properties like viscosity, permittivity or density. Thereby, each degree of loading corresponds to different viscosity values. Conventional measurements currently use invasive viscosity measurements or near-line measurements to obtain quantitative information. Avoiding invasive measurements has several severe advantages. Efforts are currently taken to provide a precise, non-invasive measurement method with equal or higher precision of the obtained results. This study investigates a method for determination of the viscosity of LOHC. Since the viscosity can retroactively derived from the degree of loading, permittivity is a target parameter as it is a suitable for determining the hydrogenation degree. This research analyses the influence of common physical properties on permittivity. The permittivity measurement system is based on a cavity resonator, an electromagnetic resonant structure, whose resonation frequency depends on its dimensions as well as the permittivity of the medium inside. For known resonator dimensions, the resonation frequency directly characterizes the permittivity. In order to determine the dependency of the permittivity on temperature and flow velocity, an experimental setup with heating device and flow test bench was designed. By varying temperature in the range of 293,15 K -393,15 K and flow velocity up to 140 mm/s, corresponding changes in the resonation frequency were measured in the hundredths of the GHz range.

Keywords: liquid organic hydrogen carriers, measurement, permittivity, viscosity., temperature, flow process

Procedia PDF Downloads 100

Authors: Bulama Alhaji Alhassan, Roselyn Odeh, Rakiya Idris Labaran, Dorcas Yemi Danladi, Faith Ochonu

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Introduction: Contraceptive use has numerous health benefits such as preventing unplanned pregnancies thereby supporting women to achieve their life goals, maintaining the ideal amount of time between pregnancies, lowering the death rate for both mothers and children and generally enhancing the lives of women and children. Despite the numerous advantages of modern contraception and numerous initiatives by the government and development partners to promote its adoption, Nigeria's use of these methods has remained persistently low. Counseling about contraception is essential to providing high-quality treatment ensuring informed choice, and voluntarism for family planning is the key. The goal of the contraceptive counseling approach known as Counseling for Choice (C4C) is to ensure that people have the agency and voice to choose the contraceptive methods that best suit their requirements by altering the way both clients and providers engage in family planning counseling sessions. Aim: To evaluate the effect of counseling for choice on Modern Contraceptive adoption and continuation among married adolescent girls aged 15-19 years in 61 health facilities, within a 6-month period in Northern Nigeria. Methodology: Data from the NDHIS was obtained from selected facilities Pre & Post commencement of C4C intervention from 36 facilities Kaduna and 25 Nasarawa Matasan Matan Arewa (MMA) core implementation states putting into consideration the specific period of initiation of intervention, six months after deployment of the C4C, data was obtained from these facilities for post analysis. Data was analyzed on SPSS using paired sample t-test. Result: C4C resulted to improved access to FP services via increasing contraceptive adoption and continued used by 15% and 27% respectively (p<0.05) in Nasarawa state. While in Kaduna state we observed 11% and 28% improvement in adoption and continued use respectively as well with statistical significance (p<0.05) depicting that the increase is highly correlated (0.99 Nasarawa and 0.75 Kaduna) with the C4C intervention where the provider uses the NORMAL AND 3Ws Rubric to explain to the client in a simplified manner what to do with chosen method, what to expect with her method of adoption and when to return for a refill. Conclusion: In Northern Nigeria, it was observed that most clients discontinue their methods due to bleeding side effect and that was related to lack of appropriate and comprehensive information during counselling about what to expect with the clients method of adoption but with the intervention of the program, through capacity strengthening of PHC providers on counselling skills using the Counselling for Choice, it has helped to improve modern contraceptive uptake among young married women in northern Nigeria.

Keywords: continuation, counselling, uptake, adolescent, modern & implementation

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Authors: Christopher Reichstein, Ralf-Christian Härting, Martina Häußler

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With a continuously increasing speed of information exchange on the World Wide Web, retailers in the E-Commerce sector are faced with immense possibilities regarding different online purchase processes like dynamic price settings. By use of Dynamic Pricing, retailers are able to set short time price changes in order to optimize producer surplus. The empirical research illustrates the basics of Dynamic Pricing and identifies six influencing factors of Dynamic Pricing. The results of a structural equation modeling approach show five main drivers increasing the potential of dynamic price settings in the E-Commerce. Influencing factors are the knowledge of customers’ individual willingness to pay, rising sales, the possibility of customization, the data volume and the information about competitors’ pricing strategy.

Keywords: e-commerce, empirical research, experts, dynamic pricing (DP), influencing factors, potentials

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Authors: Sabit Horoz, Ahmet Ekicibil, Omer Sahin, M. Akyol

Abstract:

In this study, CdZnS and Ni-doped CdZnS quantum dots(QDs) were prepared by the wet-chemical method at room temperature using mercaptoethanol as a capping agent. The structural and magnetic properties of the CdZnS and CdZnS doped with different concentrations of Ni QDs were examined by XRD and magnetic susceptibility measurements, respectively. The average particles size of cubic QDs obtained by full-width half maxima (FWHM) analysis, increases with increasing doping concentrations. The investigation of the magnetic properties showed that the Ni-doped samples exhibit signs of ferromagnetism, on the other hand, un-doped CdZnS is diamagnetic.

Keywords: un-doped and Ni doped CdZnS Quantum Dots (QDs), co-precipitation method, structural and optical properties of QDs, diluted magnetic semiconductor materials (DMSMs)

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Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

Abstract:

In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation

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Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

Abstract:

In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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Authors: Ramandeep Kaur, Gurjit Singh Bhathal

Abstract:

Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

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Authors: Filali Kamel, Sbartai Badreddine

Abstract:

The cyclic resistance curves developed by Andrus and Stokoe related to shear wave velocity case history databases are frequently used in accordance with the assumption of the Seed and Idriss simplified procedure. These cyclic resistance curves were deduced using a database according to the cyclic stress ratio (CSR) proposed by Seed and Idriss. Their approach is founded on the hypothesis that the dynamic cyclic shear stress (τd) is always less than that given by the simplified procedure (τr), as deduced by Seed and Idriss through their simplifying assumptions (rd= τd / τr <1). In 2017, Filali and Sbartai demonstrated that rd can often exceed 1, and they proposed a correction for the CSR in cases where rd > 1. Therefore, the correction of CSR implies that the cyclic resistance ratio (CRR) must also be corrected because it is defined by the boundary curve, which separates the liquefied and nonliqueified cases plotted using the original CSR of Seed and Idriss on which values of CRR are equal to CSR. For this purpose, in the context of this study, we have proposed in the range when the peak ground acceleration is ≤0.30g, which corresponds to rd>1, a modified boundary curve in accordance with the corrected version of the simplified method, which provides the safest case, generalize its use for any used earthquakes and allows the simplified method to be the more conservative.

Keywords: liquefaction, soil, earthquake, simplified method, cyclic stress ratio, cyclique resistance ratio

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