Search results for: vector density

Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

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The study used secondary data from foreign and local organizations to explore major challenges and opportunities abound in Information Communication. The study aimed at exploring the tie between tele density (network coverage area) and the number of network subscriptions, probing if the degree of consumer complaints varies significantly among network providers, and assessing if network subscriptions do significantly influence the sector’s GDP contribution. Methods used for data analysis include Pearson product-moment correlation and regression analysis, and the Analysis of Variance (ANOVA) as well. At a two-tailed test of 0.05 confidence level, the results of findings established about 85.6% of network subscriptions were explained by tele density (network coverage area), and the number of network subscriptions; Consumer Complaints’ degree varied significantly among network providers as 80.158291 (F calculated) > 3.490295 (F critical) with very high confidence associated p-value = 0.000000 which is < 0.05; and finally, 65% of the nation’s GDP was explained by network subscription to show a high association.

Keywords: tele density, subscription, network coverage, information communication, consumer

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Authors: Zeinab Jokar, Mohammad Reza Moslemi

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In this work, we study the behavior of introducing atomic size vacancy in a graphene nanoribbon superlattice. Our investigations are based on the density functional theory (DFT) with the Local Density Approximation in Atomistix Toolkit (ATK). We show that, in addition to its shape, the position of vacancy has a major impact on the electrical properties of a graphene nanoribbon superlattice. We show that the band gap of an armchair graphene nanoribbon may be tuned by introducing an appropriate periodic pattern of vacancies. The band gap changes in a zig-zag manner similar to the variation of the band gap of a graphene nanoribbon by changing its width.

Keywords: AGNR, antidot, atomistic toolKit, vacancy

Procedia PDF Downloads 1006

Authors: Anthony Chidi Ezika, Gbolahan Joseph Adekoya, Emmanuel Rotimi Sadiku, Yskandar Hamam, Suprakas Sinha Ray

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High-energy-density polymer/ceramic composites require a high breakdown strength and dielectric constant. Interface polarization and electric percolation are responsible for the high dielectric constant. In order to create composite dielectrics, high conductivity ceramic particles are combined with polymers to increase the dielectric constant. In this study, bonding and the non-uniform distribution of charges in the ceramic/ceramic interface zone are investigated using density functional theory (DFT) modeling. This non-uniform distribution of charges is intended to improve the ceramic/ceramic interface's dipole polarization (dielectric response). The interfacial chemical bond formation can also improve the structural stability of the hybrid filler and, consequently, of the composite films. To comprehend the electron-transfer process, the density of state and electron localization function of the PPy with hybrid fillers are also studied. The polymer nanocomposite is anticipated to provide a suitable dielectric response for energy storage applications.

Keywords: energy storage, V₂C/ ZnS hybrid, polypyrrole, MXene, nanocomposite, dielectric

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Authors: Tatipamula Samiksha Goud, .A.Naveena, M.sresta

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Traffic congestion is a major issue in many cities throughout the world, particularly in urban areas, and it is past time to switch from a fixed timer mode to an automated system. The current traffic signalling system is a fixed-time system that is inefficient if one lane is more functional than the others. A structure for an intelligent traffic control system is being designed to address this issue. When traffic density is higher on one side of a junction, the signal's green time is extended in comparison to the regular time. This study suggests a technique in which the signal's time duration is assigned based on the amount of traffic present at the time. Infrared sensors can be used to do this.

Keywords: infrared sensors, micro-controllers, LEDs, oscillators

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Authors: Ahmad Absetan, Mahdi Nooshyar

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The importance map is an image-based measure and is a core part of the resizing algorithm. Importance measures include image gradients, saliency and entropy, as well as high level cues such as face detectors, motion detectors and more. In this work we proposed a new method to calculate the importance map, the importance map is generated automatically using a novel combination of image edge density and Harel saliency measurement. Experiments of different type images demonstrate that our method effectively detects prominent areas can be used in image resizing applications to aware important areas while preserving image quality.

Keywords: content-aware image resizing, visual saliency, edge density, image warping

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

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Authors: K. Rattawan, W. Intagun, W. Kanoksilapatham

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Objective of this research is to study effect of coffee grounds on physical and heating value properties of sugarcane bagasse pellets. The coffee grounds were tested as an additive for pelletizing process of bagasse pellets. Pelletizing was performed using a Flat–die pellet mill machine. Moisture content of raw materials was controlled at 10-13%. Die temperature range during the process was 75-80 ^oC. Physical characteristics (bulk density and durability) of the bagasse pellet and pellets with 1-5% coffee ground were determined following the standard assigned by the Pellet Fuel Institute (PFI). The results revealed increasing values of 648±3.4, 659 ± 3.1, 679 ± 3.3 and 685 ± 3.1 kg/m³ (for pellet bulk density); and 98.7 ± 0.11, 99.2 ± 0.26, 99.3 ± 0.19 and 99.4 ± 0.07% (for pellet durability), respectively. In addition, the heating values of the coffee ground supplemented pellets (15.9 ± 1.16, 17.0 ± 1.23 and 18.8 ± 1.34 MJ/kg) were improved comparing to the non-supplemented control (14.9 ± 1.14 MJ/kg), respectively. The results indicated that both the bulk density and durability values of the bagasse pellets were increased with the increasing proportion of the coffee ground additive.

Keywords: bagasse, coffee grounds, pelletizing, heating value, sugar cane bagasse

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Authors: Juan Patricio Ibáñez, Exequiel López

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A method for synthesizing copper nanoparticles through an electrochemical approach is proposed, employing surfactants to stabilize the size of the newly formed nanoparticles. The electrolyte was made up of a matrix of H₂SO₄ (190 g/L) having Cu²⁺ (from 3.2 to 9.5 g/L), sodium dodecyl sulfate -SDS- (from 0.5 to 1.0 g/L) and Tween 80 (from 0 to 7.5 mL/L). Tween 80 was used in a molar relation of 1 to 1 with SDS. A glass cell was used, which was in a thermostatic water bath to keep the system temperature, and the electrodes were cathodic copper as an anode and stainless steel 316-L as a cathode. This process was influenced by the control exerted through the initial copper concentration in the electrolyte and the applied current density. Copper nanoparticles of electrolytic purity, exhibiting a spherical morphology of varying sizes with low dispersion, were successfully produced, contingent upon the chemical composition of the electrolyte and current density. The minimum size achieved was 3.0 nm ± 0.9 nm, with an average standard deviation of 2.2 nm throughout the entire process. The deposited copper mass ranged from 0.394 g to 1.848 g per hour (over an area of 25 cm²), accompanied by an average Faradaic efficiency of 30.8% and an average specific energy consumption of 4.4 kWh/kg. The chemical analysis of the product employed X-ray powder diffraction (XRD), while physical characteristics such as size and morphology were assessed using atomic force microscopy (AFM). It was identified that the initial concentration of copper and the current density are the variables defining the size and dispersion of the nanoparticles, as they serve as reactants in the cathodic half-reaction. The presence of surfactants stabilizes the nanoparticle size as their molecules adsorb onto the nanoparticle surface, forming a thick barrier that prevents mass transfer with the exterior and halts further growth.

Keywords: copper nanopowder, electrochemical synthesis, current density, surfactant stabilizer

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine

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Authors: Judith Mogouong, Philippe Constant, Robert Lavallee, Claude Guertin

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The emerald ash borer (EAB) is an exotic wood borer insect native from China, which is associated with important environmental and economic damages in North America. Beetles are known to be vectors of microbial communities related to their adaptive capacities. It is now established that environmental stress factors may induce physiological events on the host trees, such as phytochemical changes. Consequently, that may affect the establishment comportment of herbivorous insect. Considering the number of insects collected on ash trees (insects’ density) as an abiotic factor related to stress damage, the aim of our study was to explore the dynamic of EAB gut microbial community genome (microbiome) when facing that factor and to monitor its diversity. Insects were trapped using specific green Lindgren© traps. A gradient of the captured insect population along the St. Lawrence River was used to create three levels of insects’ density (low, intermediate, and high). After dissection, total DNA extracted from insect guts of each level has been sent for amplicon sequencing of bacterial 16S rRNA gene and fungal ITS2 region. The composition of microbial communities among sample appeared largely diversified with the Simpson index significantly different across the three levels of density for bacteria. Add to that; bacteria were represented by seven phyla and twelve classes, whereas fungi were represented by two phyla and seven known classes. Using principal coordinate analysis (PCoA) based on Bray Curtis distances of 16S rRNA sequences, we observed a significant variation between the structure of the bacterial communities depending on insects’ density. Moreover, the analysis showed significant correlations between some bacterial taxa and the three classes of insects’ density. This study is the first to present a complete overview of the bacterial and fungal communities associated with the gut of EAB base on culture-independent methods, and to correlate those communities with a potential stress factor of the host trees.

Keywords: gut microbiome, DNA, 16S rRNA sequences, emerald ash borer

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Authors: M. Adabi, A. Amadeh

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Electrodeposition is known as a relatively economical and simple technique commonly used for preparation of metallic and composite coatings. Electrodeposited composite coatings produced by dispersion of particles into the metal matrix show better properties than pure metallic coatings. In recent years, many researches were carried out on Ni matrix coatings reinforced by ceramic particles such as Ni-SiC, Ni-Al2O3, Ni-WC, Ni-CeO2, Ni-ZrO2, Ni-TiO2 to improve their corrosion and wear resistance. However, little effort has been made on incorporation of metal particles into Ni matrix. Therefore, the aim of this work was to produce Ni–Al composite coating on 6061 aluminum alloy by pulse plating and to investigate the effects of electrodeposition parameters, e.g. concentration Al particles in the electrolyte and current density, on composition and corrosion resistance of the composite coatings. The morphology and corrosion behavior of the coated 6061 Al alloys were studied by means of scanning electron microscope (SEM) equipped with energy dispersive X-ray spectrometer (EDS) and potentiodynamic polarization method, respectively. The results indicated that the addition of Al particles up to 50 g L-1 increased the amount of co-deposited Al particles in nickel matrix. It is also observed that the incorporation of Al particles decreased with increasing current density. Meanwhile, the corrosion resistance of the coatings shows an increment by increasing the content of Al particles into nickel matrix.

Keywords: Ni-Al composite coating, current density, corrosion resistance

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Authors: Muhammad Naveed, Sohail Yousaf, Zahir Ahmad Zahir, Birgit Mitter, Angela Sessitsch

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Most bacterial endophytes originate from the soil and enter plants via the roots followed by further spread through the inner tissues. The mechanisms allowing bacteria to colonize plants endophytically are still poorly understood for most bacterial and plant species. Specific bacterial functions are required for plant colonization, but also the plant itself is a determining factor as bacterial ability to establish endophytic populations is very often dependent on the plant genotype (cultivar) and inoculums density. The effect of inoculum density (107, 108, 109 CFU mL-1) of Burkholderia phytofirmans strain PsJN was evaluated on growth and endophytic colonization of different maize and potato cultivars under axenic and natural soil conditions. PsJN inoculation significantly increased maize seedling growth and tuber yield of potato at all inoculum density compared to uninoculated control. Under axenic condition, PsJN inoculation (108 CFU mL-1) significantly improved the germination, root/shoot length and biomass up to 62, 115, 98 and 135% of maize seedling compared to uninoculated control. In case of potato, PsJN inoculation (109 CFU mL-1) showed maximum response and significantly increased root/shoot biomass and tuber yield under natural soil condition. We confirmed that PsJN is able to colonize the rhizosphere, roots and shoots of maize and potato cultivars. The endophytic colonization increased linearly with increasing inoculum density (within a range of 8 x 104 – 3 x 107 CFU mL-1) and were highest for maize (Morignon) and potato (Romina) as compared to other cultivars. Efficient colonization of cv. Morignon and Romina by strain PsJN indicates the specific cultivar colonizing capacity of the bacteria. The findings of the study indicate the non-significant relationship between colonization and plant growth promotion in maize under axenic conditions. However, the inoculum level (109 CFU mL-1) that promoted colonization of rhizosphere and plant interior (endophytic) also best promoted growth and tuber yield of potato under natural soil conditions.

Keywords: crop genotype, inoculum density, Burkholderia phytofirmans PsJN, colonization, growth, potato

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Authors: P. L. Cheng, I. N. Umar

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Online discussion forum is a popular e-learning technique that allows participants to interact and construct knowledge. This study aims to examine the levels of participation, categories of participants and the structure of their interactions in a forum. A convenience sampling of one course coordinator and 23 graduate students was selected in this study. The forums’ log file and the Social Network Analysis software were used in this study. The analysis reveals 610 activities (including viewing forum’s topic, viewing discussion thread, posting a new thread, replying to other participants’ post, updating an existing thread and deleting a post) performed by them in this forum, with an average of 3.83 threads posted. Also, this forum consists of five at-risk participants, six bridging participants, four isolated participants and five leaders of information. In addition, the network density value is 0.15 and there exist five reciprocal interactions in this forum. The closeness value varied between 28 and 68 while the eigen vector centrality value varied between 0.008 and 0.39. The finding indicates that the participants tend to listen more rather than express their opinions in the forum. It was also revealed that those who actively provide supports in the discussion forum were not the same people who received the most responses from their peers. This study found that cliques do not exist in the forum and the participants are not selective to whom they response to, rather, it was based on the content of the posts made by their peers. Based upon the findings, further analysis with different method and population, larger sample size and a longer time frame are recommended.

Keywords: e-learning, learning management system, online forum, social network analysis

Procedia PDF Downloads 390

Authors: Svetlana V. Topolyanskaya, Tatyana A. Eliseeva, Olga N. Vakulenko, Leonid I. Dvoretski

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Introduction: Limited data are available on osteoporosis in centenarians. Therefore, we evaluated bone mineral density in long-living patients with coronary artery disease (CAD). Methods: 202 patients hospitalized with CAD were enrolled in this cross-sectional study. The patients' age ranged from 90 to 101 years. The majority of study participants (64.4%) were women. The main exclusion criteria were any disease or medication that can lead to secondary osteoporosis. Bone mineral density (BMD) was measured by dual-energy X-ray absorptiometry. Results: Normal lumbar spine BMD was observed in 40.9%, osteoporosis – in 26.9%, osteopenia – in 32.2% of patients. Normal proximal femur BMD values were observed in 21.3%, osteoporosis – in 39.9%, and osteopenia – in 38.8% of patients. Normal femoral neck BMD was registered only in 10.4% of patients, osteoporosis was observed in 60.4%, osteopenia in 29.2%. Significant positive correlation was found between all BMD values and body mass index of patients (p < 0.001). Positive correlation was registered between BMD values and serum uric acid (p=0.0005). The likelihood of normal BMD values with hyperuricemia increased 3.8 times, compared to patients with normal uric acid, who often have osteoporosis (Odds Ratio=3.84; p = 0.009). Positive correlation was registered between all BMD values and body mass index (p < 0.001). Positive correlation between triglycerides levels and T-score (p=0.02), but negative correlation between BMD and HDL-cholesterol (p=0.02) were revealed. Negative correlation between frailty severity and BMD values (p=0.01) was found. Positive correlation between BMD values and functional abilities of patients assessed using Barthel index (r=0,44; p=0,000002) and IADL scale (r=0,36; p=0,00008) was registered. Fractures in history were observed in 27.6% of patients. Conclusions: The study results indicate some features of BMD in long-livers. In the study group, significant relationships were found between bone mineral density on the one hand, and patients' functional abilities on the other. It is advisable to further study the state of bone tissue in long-livers involving a large sample of patients.

Keywords: osteoporosis, bone mineral density, centenarians, coronary artery disease

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

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Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

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This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

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Authors: L. Yettou

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In this study, the calculations of proton emission spectra produced by ⁶³Cu(n,xp) and ⁶⁵Cu(n,xp) reactions are used in the framework of preequilibrium models using the EMPIRE code and TALYS code. Exciton Model predidtions combined with the Kalbach angular distribution systematics and the Hybrid Monte Carlo Simulation (HMS) were used. The effects of levels densities and those of a-parameter have been investigated for our calculations. The comparison with experimental data shows clear improvement over the Exciton Model and HMS calculations.

Keywords: Preequilibrium models , level density, level density a-parameter., Empire code, Talys code.

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Authors: Soner Guler, Fuat Korkut

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Recently, the using of lightweights concretes in construction sector is rapidly increasing all over the world. Faster construction, low density and thermal transmitting coefficient and high fire resistance are the remarkable characteristics of the lightweight concretes. Lightweight concrete can be described as a type of concrete which enhance the volume of the mixture while giving additional advantages such as to reduce the dead weight of the structures. It is lighter than the conventional concrete. The use of lightweight concrete has been widely spread across countries such as USA, United Kingdom, and Sweden. In this study, the necessity of the using of lightweights concretes in the construction sector is emphasized and evaluated briefly for the architectures and civil engineers.

Keywords: lightweights concretes, low density, low thermal coefficient, construction sector

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Authors: G. Patricia Abdel Rahim, Jairo Arbey Rodriguez M, María Guadalupe Moreno Armenta

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The present study shows the structural, electronic and magnetic properties of magnesium (Mg) and bismuth (Bi) in a supercell (1X1X5). For both materials were studied in five crystalline structures: rock salt (NaCl), cesium chloride (CsCl), zinc-blende (ZB), wurtzite (WZ), and nickel arsenide (NiAs), using the Density Functional Theory (DFT), the Generalized Gradient Approximation (GGA), and the Full Potential Linear Augmented Plane Wave (FP-LAPW) method. By means of fitting the Murnaghan's state equation we determine the lattice constant, the bulk modulus and it's derived with the pressure. Also we calculated the density of states (DOS) and the band structure.

Keywords: bismuth, magnesium, pseudo-potential, supercell

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Authors: Hossein Asgarzadeh, Ayoub Osmani, Farrokh Asadzadeh, Mohammad Reza Mosaddeghi

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This study was conducted to evaluate the topsoil and subsoil physical quality using relative bulk density (RBD) in Urmia plain in Iran. Undisturbed samples were collected from two layers (topsoil and subsoil) of thirty agricultural soils. Categories of 0.72 ≥ RBD (low degree of compactness), 0.82 > RBD > 0.72 (moderate/optimum degree of compactness), and RBD ≥ 0.82 (high degree of compactness) were used to evaluate soil physical quality (SPQ). Two topsoils had a low degree of compactness, fourteen topsoils had an optimum degree of compactness, and the rest (i.e., fourteen topsoils) had a high degree of compactness. Only one subsoil had an optimum degree of compactness, and twenty-eight subsoils (i.e., 93%) had a high degree of compactness, indicating poor SPQ of the subsoil layer in the studied region. It seems that conventional tillage in the past decades destroyed the pore system in the majority of studied subsoils. The high degree of compactness would reduce soil aeration and increase soil penetration resistance which could restrict root and plant growth. Conversely, a low degree of soil compactness is expected to reduce the root-soil contact.

Keywords: compactness, relative bulk density, soil physical quality

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Authors: Robert Jacobsen

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Flood inundation maps (FIMs) are an essential tool in communicating flood threat scenarios to the public as well as in floodplain governance. With an increasing demand for online raster FIMs, the FIM State-of-the-Practice (SOP) is rapidly advancing to meet the dual requirements for high-resolution and high-accuracy—or High-Definition. Importantly, today’s technology also enables the resolution of problems of local—neighborhood-scale—bias errors that often occur in FIMs, even with the use of SOP two-dimensional flood modeling. To facilitate the development of HD-FIMs, a new GIS method--Raster Adjustment with Scenario Profiles, RASPTM—is described for adjusting kernel raster FIMs to match refined scenario profiles. With RASPTM, flood professionals can prepare HD-FIMs for a wide range of scenarios with available kernel rasters, including kernel rasters prepared from vector FIMs. The paper provides detailed procedures for RASPTM, along with an example of applying RASPTM to prepare an HD-FIM for the August 2016 Flood in Louisiana using both an SOP kernel raster and a kernel raster derived from an older vector-based flood insurance rate map. The accuracy of the HD-FIMs achieved with the application of RASPTM to the two kernel rasters is evaluated.

Keywords: hydrology, mapping, high-definition, inundation

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Authors: Ali Ashtiani, Hamid Shirazi

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This paper reviews the status of existing practice and research related to measuring pavement cracking and using crack density as a pavement surface evaluation protocol. Crack density for pavement evaluation is currently not widely used within the airport community and its use by the highway community is limited. However, surface cracking is a distress that is closely monitored by airport staff and significantly influences the development of maintenance, rehabilitation and reconstruction plans for airport pavements. Therefore crack density has the potential to become an important indicator of pavement condition if the type, severity and extent of surface cracking can be accurately measured. A pavement distress survey is an essential component of any pavement assessment. Manual crack surveying has been widely used for decades to measure pavement performance. However, the accuracy and precision of manual surveys can vary depending upon the surveyor and performing surveys may disrupt normal operations. Given the variability of manual surveys, this method has shown inconsistencies in distress classification and measurement. This can potentially impact the planning for pavement maintenance, rehabilitation and reconstruction and the associated funding strategies. A substantial effort has been devoted for the past 20 years to reduce the human intervention and the error associated with it by moving toward automated distress collection methods. The automated methods refer to the systems that identify, classify and quantify pavement distresses through processes that require no or very minimal human intervention. This principally involves the use of a digital recognition software to analyze and characterize pavement distresses. The lack of established protocols for measurement and classification of pavement cracks captured using digital images is a challenge to developing a reliable automated system for distress assessment. Variations in types and severity of distresses, different pavement surface textures and colors and presence of pavement joints and edges all complicate automated image processing and crack measurement and classification. This paper summarizes the commercially available systems and technologies for automated pavement distress evaluation. A comprehensive automated pavement distress survey involves collection, interpretation, and processing of the surface images to identify the type, quantity and severity of the surface distresses. The outputs can be used to quantitatively calculate the crack density. The systems for automated distress survey using digital images reviewed in this paper can assist the airport industry in the development of a pavement evaluation protocol based on crack density. Analysis of automated distress survey data can lead to a crack density index. This index can be used as a means of assessing pavement condition and to predict pavement performance. This can be used by airport owners to determine the type of pavement maintenance and rehabilitation in a more consistent way.

Keywords: airport pavement management, crack density, pavement evaluation, pavement management

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Authors: George Eduful, Yuanyuan Fan, Ahmed Abu-Siada

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Ferroresonance poses a substantial threat to the quality and reliability of power distribution systems due to its inherent characteristics of sustained overvoltages and currents. This paper aims to enhance the understanding and reduce the ferroresonance threat by investigating the susceptibility of different transformer configurations using MATLAB/Simulink simulations. To achieve this, four 200 kVA transformers with different vector groups (D-Yn, Yg-Yg, Yn-Yn, and Y-D11) and core types (3-limb, 5-limb, single-phase) were systematically exposed to controlled ferroresonance conditions. The impact of varying the length of the 11 kV cable connected to the transformers was also examined. Through comprehensive voltage, current, and total harmonic distortion analyses, the performance of each configuration was evaluated and compared. The results of the study indicate that transformers with Y-D11 and Yg-Yg configurations exhibited lower susceptibility to ferroresonance, in comparison to those with D-Y11 and Yg-Yg configurations. This implies that the Y-D11 and Yg-Yg transformers are better suited for applications with high risks of ferroresonance. The insights provided by this study are of significant value for the strategic selection and deployment of transformers in power systems, particularly in settings prone to ferroresonance. By identifying and recommending transformer configurations that demonstrate better resilience, this paper contributes to enhancing the overall robustness and reliability of power grid infrastructure.

Keywords: about cable-connected, core type, ferroresonance, over voltages, power transformer, vector group

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

Abstract:

Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

Abstract:

Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

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Authors: S. Muthuraja Soundrapandian, C.K. Subramaniam

Abstract:

A micro Direct Methanol Fuel Cell (DMFC) of 1 cm2 active area with selective sensor materials to sense methanol for redox, has been developed. Among different Pt alloys, Pt-Sn/C was able to produce high current density and repeatability. Membrane Elecctrode Assembly (MEA) of anode catalyst Pt-Sn/C was prepared with nafion as active membrane and Pt black as cathode catalyst. The sensor’s maximum ability to detect the trace levels of methanol in ppm has been analyzed. A compact sensor set up has also been made and the characterization studies were carried out. The acceptable value of current density was derived by the cell and the results are able to fulfill the needs of DMFC technology for the practical applications.

Keywords: DMFC, sensor, MEA, Pt-Sn

Procedia PDF Downloads 140

Authors: Diego A. Romero Espinosa

Abstract:

Thermal simulations are used to evaluate comfort and energy consumption of buildings. However, the performance of different urban forms cannot be assessed precisely if an environmental control system and user schedules are considered. The outcome of such analysis would lead to conclusions that combine the building use, operation, services, envelope, orientation and density of the urban fabric. The influence of these factors varies during the life cycle of a building. The orientation, as well as the surroundings, can be considered a constant during the lifetime of a building. The structure impacts the thermal inertia and has the largest lifespan of all the building components. On the other hand, the building envelope is the most frequent renovated component of a building since it has a great impact on energy performance and comfort. Building services have a shorter lifespan and are replaced regularly. With the purpose of addressing the performance, an urban form, a specific orientation, and density, a thermal simulation method were developed. The solar irradiation is taken into consideration depending on the outdoor temperature. Incoming irradiation at low temperatures has a positive impact increasing the indoor temperature. Consequently, overheating would be the combination of high outdoor temperature and high irradiation at the façade. On this basis, the indoor temperature is simulated for a specific orientation of the evaluated urban form. Thermal inertia and building envelope performance are considered additionally as the materiality of the building. The results of different thermal zones are summarized using the 'Degree day method' for cooling and heating. During the early phase of a design process for a project, such as Masterplan, conclusions regarding urban form, density and materiality can be drawn by means of this analysis.

Keywords: building envelope, density, masterplanning, urban form

Procedia PDF Downloads 145

Authors: Jitendra Pratap, Jonathan Sivyer

Abstract:

Introduction: Dual energy/Spectral CT scanning permits simultaneous acquisition of two x-ray spectra datasets and can complement radiological diagnosis by allowing tissue characterisation (e.g., uric acid vs. non-uric acid renal stones), enhancing structures (e.g. boost iodine signal to improve contrast resolution), and quantifying substances (e.g. iodine density). However, the latter showed inconsistent results between the 2 main modes of dual energy scanning (i.e. dual source vs. dual layer). Therefore, the present study aimed to determine which technology is more accurate in quantifying iodine density. Methods: Twenty vials with known concentrations of iodine solutions were made using Optiray 350 contrast media diluted in sterile water. The concentration of iodine utilised ranged from 0.1 mg/ml to 1.0mg/ml in 0.1mg/ml increments, 1.5 mg/ml to 4.5 mg/ml in 0.5mg/ml increments followed by further concentrations at 5.0 mg/ml, 7mg/ml, 10 mg/ml and 15mg/ml. The vials were scanned using Dual Energy scan mode on a Siemens Somatom Force at 80kV/Sn150kV and 100kV/Sn150kV kilovoltage pairing. The same vials were scanned using Spectral scan mode on a Philips iQon at 120kVp and 140kVp. The images were reconstructed at 5mm thickness and 5mm increment using Br40 kernel on the Siemens Force and B Filter on Philips iQon. Post-processing of the Dual Energy data was performed on vendor-specific Siemens Syngo VIA (VB40) and Philips Intellispace Portal (Ver. 12) for the Spectral data. For each vial and scan mode, the iodine concentration was measured by placing an ROI in the coronal plane. Intraclass correlation analysis was performed on both datasets. Results: The iodine concentrations were reproduced with a high degree of accuracy for Dual Layer CT scanner. Although the Dual Source images showed a greater degree of deviation in measured iodine density for all vials, the dataset acquired at 80kV/Sn150kV had a higher accuracy. Conclusion: Spectral CT scanning by the dual layer technique has higher accuracy for quantitative measurements of iodine density compared to the dual source technique.

Keywords: CT, iodine density, spectral, dual-energy

Procedia PDF Downloads 120

Authors: Y. Seki, A. Ç. Kılıç, M. Atagür, O. Özdemir, İ. Şen, K. Sever, Ö. Seydibeyoğlu, M. Sarikanat, N. Küçükdoğan

Abstract:

Cheap and abundant waste materials have been investigated as filler materials in thermoplastic polymers instead of wood- based materials because of deforestation. Vine stem, as an agricultural waste, was used as a filler material for a thermoplastic polymer, high-density polyethylene (HDPE) in this study. Agricultural waste of vine stem was collected from Manisa region, Turkey. Vine stem at different rations was used to reinforce HDPE. The effect of vine stem loading on tensile strength and Young’s modulus of composites were obtained. It was clearly observed that tensile strength and Young’s modulus of HDPE was increased by vine stem loading. Thermal stabilities of composites were obtained by using thermogravimetric analysis. Water absorption behavior of HDPE was improved by loading vine stem into HDPE. The crystallinity index values of neat HDPE and vine stem loaded HDPE composites were investigated byX-ray diffraction analysis. From this study, it was inferred that vine stem, as an agricultural waste, can be used as a filler material for HDPE.

Keywords: waste filler, high density polyethylene, composite, composite materials

Procedia PDF Downloads 517