Search results for: slice thickness accuracy

Authors: Sofiqul Islam, V. Murugan, Prema Kumari, Hari

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Gentamicin is a broad spectrum water-soluble aminoglycoside antibiotics produced by the fermentation process of microorganism known as Micromonospora purpurea. It is widely used for the treatment of infection caused by both gram positive and gram negative bacteria. Gentamicin consists of a mixture of aminoglycoside components like C1, C1a, C2a, and C2. The molecular structure of Gentamicin and its related substances showed that it has lack of presence of chromophore group in the molecule due to which the detection of such components were quite critical and challenging. In this study, a simple Reversed Phase-High Performance Liquid Chromatographic (RP-HPLC) method using ultraviolet (UV) detector was developed and validated for quantification of the related substances present in Gentamicin drug substances. The method was achieved by using Thermo Scientific Hypersil Gold analytical column (150 x 4.6 mm, 5 µm particle size) with isocratic elution composed of methanol: water: glacial acetic acid: sodium hexane sulfonate in the ratio 70:25:5:3 % v/v/v/w as a mobile phase at a flow rate of 0.5 mL/min, column temperature was maintained at 30 °C and detection wavelength of 330 nm. The four components of Gentamicin namely Gentamicin C1, C1a, C2a, and C2 were well separated along with the related substance present in Gentamicin. The Limit of Quantification (LOQ) values were found to be at 0.0075 mg/mL. The accuracy of the method was quite satisfactory in which the % recovery was resulted between 95-105% for the related substances. The correlation coefficient (≥ 0.995) shows the linearity response against concentration over the range of Limit of Quantification (LOQ). Precision studies showed the % Relative Standard Deviation (RSD) values less than 5% for its related substance. The method was validated in accordance with the International Conference of Harmonization (ICH) guideline with various parameters like system suitability, specificity, precision, linearity, accuracy, limit of quantification, and robustness. This proposed method was easy and suitable for use for the quantification of related substances in routine analysis of Gentamicin formulations.

Keywords: reversed phase-high performance liquid chromatographic (RP-HPLC), high performance liquid chromatography, gentamicin, isocratic, ultraviolet

Procedia PDF Downloads 166

Authors: Marzie Shahini, Alireza Bagheri Sabbagh, Rasoul Mirghaderi, Paul C. Davidson

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The focus of this paper is to incorporating the slotted bolted connection into the cold-formed steel (CFS) beams with aim of increasing inelastic bending capacity through bolt slip. An extensive finite element analysis was conducted on the through plate CFS bolted connections which are equipped with the slotted hole. The studied parameters in this paper included the following: CFS beam section geometry, the value of slip force, CFS beam thickness. The numerical results indicate that CFS slotted bolted connection exhibit higher inelastic capacity in terms of ductility compare to connection with standards holes. Moreover, the effect of slip force was analysed by comparing the moment-rotation curves of different models with different slip force value. As a result, as the slip force became lower, there was a tendency for the plastic strain to extend from the CFS member to the connection region.

Keywords: slip-critical bolted connection, inelastic capacity, slotted holes, cold-formed steel, bolt slippage, slip force

Procedia PDF Downloads 434

Authors: Xiaobin Liang, Wei Liang, Laibin Zhang, Xiaoyan Guo

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Pipelines pass through coal mined gobs inevitably in the mining area, the stability of which has great influence on the safety of pipelines. After extensive literature study and field research, it was found that there are a few risk assessment methods for coal mined gob pipelines, and there is a lack of data on the gob sites. Therefore, the fuzzy comprehensive evaluation method is widely used based on expert opinions. However, the subjective opinions or lack of experience of individual experts may lead to inaccurate evaluation results. Hence the accuracy of the results needs to be further improved. This paper presents a comprehensive approach to achieve this purpose by combining bow-tie model and cloud inference. The specific evaluation process is as follows: First, a bow-tie model composed of a fault tree and an event tree is established to graphically illustrate the probability and consequence indicators of pipeline failure. Second, the interval estimation method can be scored in the form of intervals to improve the accuracy of the results, and the censored mean algorithm is used to remove the maximum and minimum values of the score to improve the stability of the results. The golden section method is used to determine the weight of the indicators and reduce the subjectivity of index weights. Third, the failure probability and failure consequence scores of the pipeline are converted into three numerical features by using cloud inference. The cloud inference can better describe the ambiguity and volatility of the results which can better describe the volatility of the risk level. Finally, the cloud drop graphs of failure probability and failure consequences can be expressed, which intuitively and accurately illustrate the ambiguity and randomness of the results. A case study of a coal mine gob pipeline carrying natural gas has been investigated to validate the utility of the proposed method. The evaluation results of this case show that the probability of failure of the pipeline is very low, the consequences of failure are more serious, which is consistent with the reality.

Keywords: bow-tie model, natural gas pipeline, coal mine gob, cloud inference

Procedia PDF Downloads 254

Authors: T. Boonraksa, B. Marungsri

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This paper presents the experimental results on role of ionic solutions affect water treeing propagation in cross-linked polyethylene insulation for high voltage cable. To study the water treeing expansion due to the ionic solutions, discs of 4mm thickness and 4cm diameter were taken from 115 kV XLPE insulation cable and were used as test specimen in this study. Ionic solutions composed of CuSO4, FeSO4, Na2SO4 and K2SO4 were used. Each specimen was immersed in 0.1 mole ionic solutions and was tested for 120 hrs. under a voltage stress at 7 kV AC rms, 1000 Hz. The results show that Na2SO4 and CuSO4solutions play an important role in the expansion of water treeing and cause degradation of the cross-linked polyethylene (XLPE) in the presence of the applied electric field.

Keywords: ionic solutions, water treeing, water treeing expansion, cross-linked polyethylene (XLPE)

Procedia PDF Downloads 390

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

Procedia PDF Downloads 174

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

Procedia PDF Downloads 141

Authors: Fabienne Samyn, Pauline Tranchard, Sophie Duquesne, Emilie Goncalves, Bruno Estebe, Serge Boubigot

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Stringent fire safety regulations are enforced in the aeronautical industry due to the consequences that potential fire event on an aircraft might imply. This is so much true that the fire issue is considered right from the design of the aircraft structure. Due to the incorporation of an increasing amount of polymer matrix composites in replacement of more conventional materials like metals, the nature of the fire risks is changing. The choice of materials used is consequently of prime importance as well as the evaluation of its resistance to fire. The fire testing is mostly done using the so-called certification tests according to standards such as the ISO2685:1998(E). The latter describes a protocol to evaluate the fire resistance of structures located in fire zone (ability to withstand fire for 5min). The test consists in exposing an at least 300x300mm² sample to an 1100°C propane flame with a calibrated heat flux of 116kW/m². This type of test is time-consuming, expensive and gives access to limited information in terms of fire behavior of the materials (pass or fail test). Consequently, it can barely be used for material development purposes. In this context, the laboratory UMET in collaboration with industrial partners has developed a horizontal and a vertical small-scale instrumented fire benches for the characterization of the fire behavior of composites. The benches using smaller samples (no more than 150x150mm²) enables to cut downs costs and hence to increase sampling throughput. However, the main added value of our benches is the instrumentation used to collect useful information to understand the behavior of the materials. Indeed, measurements of the sample backside temperature are performed using IR camera in both configurations. In addition, for the vertical set up, a complete characterization of the degradation process, can be achieved via mass loss measurements and quantification of the gasses released during the tests. These benches have been used to characterize and study the fire behavior of aeronautical carbon/epoxy composites. The horizontal set up has been used in particular to study the performances and durability of protective intumescent coating on 2mm thick 2D laminates. The efficiency of this approach has been validated, and the optimized coating thickness has been determined as well as the performances after aging. Reductions of the performances after aging were attributed to the migration of some of the coating additives. The vertical set up has enabled to investigate the degradation process of composites under fire. An isotropic and a unidirectional 4mm thick laminates have been characterized using the bench and post-fire analyses. The mass loss measurements and the gas phase analyses of both composites do not present significant differences unlike the temperature profiles in the thickness of the samples. The differences have been attributed to differences of thermal conductivity as well as delamination that is much more pronounced for the isotropic composite (observed on the IR-images). This has been confirmed by X-ray microtomography. The developed benches have proven to be valuable tools to develop fire safe composites.

Keywords: aeronautical carbon/epoxy composite, durability, intumescent coating, small-scale ‘ISO 2685 like’ fire resistance test, X-ray microtomography

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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The link between man and food plays, in the social and economic system, a central role where cultural and multidisciplinary aspects intertwine: food is not only nutrition, but also communication, culture, politics, environment, science, ethics, fashion. This multi-dimensionality has many implications in the food economy. In recent years, the consumer became more conscious about his food choices, involving a consistent change in consumption models. This change concerns several aspects: awareness of food system issues, employment of socially and environmentally conscious decision-making, food choices based on different characteristics than nutritional ones i.e. origin of food, how it’s produced, and who’s producing it. In this frame the ‘consumption choices’ and the ‘interests of the citizen’ become one part of the others. The figure of the ‘Citizen Consumer’ is born, a responsible and ethically motivated individual to change his lifestyle, achieving the goal of sustainable consumption. Simultaneously the branding, that before was guarantee of the product quality, today is questioned. In order to meet these needs, Agri-Food companies are developing specific product lines that follow two main philosophies: ‘Back to basics’ and ‘Less is more’. However, the issue of ethical behavior does not seem to find an adequate on market offer. Most likely due to a lack of attention on the communication strategy used, very often based on market logic and rarely on ethical one. The label in its classic concept of ‘clean labeling’ can no longer be the only instrument through which to convey product information and its evolution towards a concept of ‘clear label’ is necessary to embrace ethical and transparent concepts in progress the process of democratization of the Food System. The implementation of a voluntary traceability path, relying on the technological models of the Internet of Things or Industry 4.0, would enable the Agri-Food Supply Chain to collect data that, if properly treated, could satisfy the information need of consumers. A change of approach is therefore proposed towards Agri-Food traceability that is no longer intended as a tool to be used to respond to the legislator, but rather as a promotional tool useful to tell the company in a transparent manner and then reach the slice of the market of food citizens. The use of mobile technology can also facilitate this information transfer. However, in order to guarantee maximum efficiency, an appropriate communication model based on the ethical communication principles should be used, which aims to overcome the pipeline communication model, to offer the listener a new way of telling the food product, based on real data collected through processes traceability. The Citizen Consumer is therefore placed at the center of the new model of communication in which he has the opportunity to choose what to know and how. The new label creates a virtual access point capable of telling the product according to different point of views, following the personal interests and offering the possibility to give several content modalities to support different situations and usability.

Keywords: agri food traceability, agri-food transparency, clear label, food system, internet of things

Procedia PDF Downloads 162

Authors: K. Rajalakshmi, A. Vasudevan

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The performance of Fibre Reinforced Polymer composite with the nano-ceramic particle as function of time and thickness of laminate which is subjected to ballistic impact and quasi-static punch-shear loading is investigated. The material investigated is made up of several layers of Kevlar fibres which are fabricated with nano-ceramic particles and epoxy resin by compression moulding. The ballistic impact and quasi-static punch-shear loading are studied experimentally and numerically. The failure mechanism is observed using scanning electron microscope (SEM). The result obtained in the experiment and numerical studies are compared. Due to nano size of the ceramic particle, the strength to weight ratio and penetrating resistance will improve in Fibre Reinforced Polymer composite which will have better impact property compared to ceramic plates.

Keywords: ballistic impact, Kevlar, nano ceramic, penetration, polymer composite, shear plug

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Authors: A. Mostafa

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This paper presents a numerical study on determination of ballistic limit velocity (V₅₀) of stainless steel 304 (SS 304) used in manufacturing security screens. The simulated ballistic impact tests were conducted on clamped sheets with different thicknesses using ABAQUS/Explicit nonlinear finite element (FE) package. The ballistic limit velocity was determined using three approaches, namely: numerical tests based on material properties, FE calculated residual velocities and FE calculated residual energies. Johnson-Cook plasticity and failure criterion were utilized to simulate the dynamic behaviour of the SS 304 under various strain rates, while the well-known Lambert-Jonas equation was used for the data regression for the residual velocity and energy model. Good agreement between the investigated numerical methods was achieved. Additionally, the dependence of the ballistic limit velocity on the sheet thickness was observed. The proposed approaches present viable and cost-effective assessment methods of the ballistic performance of SS 304, which will support the development of robust security screen systems.

Keywords: ballistic velocity, stainless steel, numerical approaches, security screen

Procedia PDF Downloads 169

Authors: Naina Mahajan, Bikram Pal Kaur

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The purpose of traffic accident analysis is to find the possible causes of an accident. Road accidents cannot be totally prevented but by suitable traffic engineering and management the accident rate can be reduced to a certain extent. This paper discusses the classification techniques C4.5 and ID3 using the WEKA Data mining tool. These techniques use on the NH (National highway) dataset. With the C4.5 and ID3 technique it gives best results and high accuracy with less computation time and error rate.

Keywords: C4.5, ID3, NH(National highway), WEKA data mining tool

Procedia PDF Downloads 341

Authors: M. A. Aleem, M. S. Awan

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Flat spiral coil for electromagnetic forming system has been modelled in FEMM 4.2 software. Copper strip was chosen as the material for designing the actuator coil. Relationship between height to width ratio (S-factor) of the copper strip and coil’s performance has been studied. Magnetic field intensities, eddy currents, and Lorentz force were calculated for the coils that were designed using six different 'S-factor' values (0.65, 0.75, 1.05, 1.25, 1.54 and 1.75), keeping the cross-sectional area of strip the same. Results obtained through simulation suggest that actuator coil with S-factor ~ 1 shows optimum forming performance as it exerts maximum Lorentz force (84 kN) on work piece. The same coils were fabricated and used for electromagnetic sheet forming experiments. Aluminum 6061 sheets of thickness 1.5 mm have been formed using different voltage levels of capacitor bank. Smooth forming profiles were obtained with dome heights 28, 35 and 40 mm in work piece at 800, 1150 and 1250 V respectively.

Keywords: FEM modelling, electromagnetic forming, spiral coil, Lorentz force

Procedia PDF Downloads 289

Authors: Minna Theres James, Nirmal K Sebastian, Shoubhik Mandal, Pramita Mishra, R Ganesan, P S Anil Kumar

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We report the temperature-dependent evolution of Raman spectra of type-II Dirac semimetal (DSM) NiTe2 (001) in the form of bulk single crystal and a nanoflake (200 nm thick) for the first time. A physical model that can quantitatively explain the evolution of out of plane A1g and in-plane E1g Raman modes is used. The non-linear variation of peak positions of the Raman modes with temperature is explained by anharmonic three-phonon and four-phonon processes along with thermal expansion of the lattice. We also observe prominent effect of electron-phonon coupling from the variation of FWHM of the peaks with temperature, indicating the metallicity of the samples. Raman mode E1 1g corresponding to an in plane vibration disappears on decreasing the thickness from bulk to nanoflake.

Keywords: raman spectroscopy, type 2 dirac semimetal, nickel telluride, phonon-phonon coupling, electron phonon coupling, transition metal dichalcogonide

Procedia PDF Downloads 119

Authors: Ciro Sobrinho Campolina Martins, Halison da Silva Pereira, Vitor Mainenti Leal Lopes

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Unmanned Aerial vehicles (UAVs) has been used in a wide range of applications, from precise agriculture monitoring for irrigation and fertilization to military attack missions. Long range performance is required for many of these applications. Tailless aircrafts are commonly used as long-range configurations and, due to its small amount of stability, the airfoil shape design of its wings plays a central role on the performance of the airplane. In this work, a new family of flying wing airfoils is designed for low Reynolds number flows, typical of small-middle UAVs. Camber, thickness and their maximum positions in the chord are variables used for the airfoil geometry optimization. Aerodynamic non-dimensional coefficients were obtained by the well-established Panel Method. High efficient airfoils with small pitch moment coefficient are obtained from the analysis described and its aerodynamic polars are plotted.

Keywords: airfoil design, flying wing, low Reynolds number, tailless aircraft, UAV

Procedia PDF Downloads 632

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

Procedia PDF Downloads 178

Authors: Panatda Intanin, Sangutid Thongsawad, Chirapha Tannanonta, Todsaporn Fuangrod

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Stereotactic radiosurgery (SRS) is a highly precision delivery technique that requires comprehensive quality assurance (QA) tests prior to treatment delivery. An isocenter of delivery beam plays a critical role that affect the treatment accuracy. The uncertainty of isocenter is traditionally accessed using circular cone equipment, Winston-Lutz (WL) phantom and film. This technique is considered time consuming and highly dependent on the observer. In this work, the development of multileaf collimator (MLC)-based isocenter verification tool using electronic portal imaging device (EPID) was proposed and evaluated. A mechanical isocenter alignment with ball bearing diameter 5 mm and circular cone diameter 10 mm fixed to gantry head defines the radiation field was set as the conventional WL test method. The conventional setup was to compare to the proposed setup; using MLC (10 x 10 mm) to define the radiation filed instead of cone. This represents more realistic delivery field than using circular cone equipment. The acquisition from electronic portal imaging device (EPID) and radiographic film were performed in both experiments. The gantry angles were set as following: 0°, 90°, 180° and 270°. A software tool was in-house developed using MATLAB/SIMULINK programming to determine the centroid of radiation field and shadow of WL phantom automatically. This presents higher accuracy than manual measurement. The deviation between centroid of both cone-based and MLC-based WL tests were quantified. To compare between film and EPID image, the deviation for all gantry angle was 0.26±0.19mm and 0.43±0.30 for cone-based and MLC-based WL tests. For the absolute deviation calculation on EPID images between cone and MLC-based WL test was 0.59±0.28 mm and the absolute deviation on film images was 0.14±0.13 mm. Therefore, the MLC-based isocenter verification using EPID present high sensitivity tool for SRS QA.

Keywords: isocenter verification, quality assurance, EPID, SRS

Procedia PDF Downloads 156

Authors: Reza Abbasi, Ahmad Hamidi Benam

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Shell structures have many geometrical variables that modify some of these parameters to improve the mechanical behavior of the shell. On the other hand, the behavior of such structures depends on their geometry rather than on mass. Optimization techniques are useful in finding the geometrical shape of shell structures to improve mechanical behavior, especially to prevent or reduce bending anchors. The overall objective of this research is to optimize the shape of concrete shells using the thickness and height parameters along the reference curve and the overall shape of this curve. To implement the proposed scheme, the geometry of the structure was formulated using nonlinear curves. Shell optimization was performed under equivalent static loading conditions using the modified bird community algorithm. The results of this optimization show that without disrupting the initial design and with slight changes in the shell geometry, the structural behavior is significantly improved.

Keywords: concrete shells, shape optimization, spinless curves, modified particle community algorithm

Procedia PDF Downloads 237

Authors: Ayman Hegab

Abstract:

Dystonia is a neurological motor disorder characterized by involuntary and uncontrollable muscle contractions, tension, twisting, and tremors. The aim of the present study was to analyze the improvement in dystonic contractions in patients with dystonia following the use of a Hegab temporomandibular joint splint (HTS). The Fahn-Marsden Dystonia Movement Scale (DMS) and Disability Scale were used in the current study to evaluate dystonia. An HTS with a thickness ranging from 4 to 6 mm was used to treat the patients enrolled in the study. The final sample comprised 14 patients (10 female and four male) with mean (range) ages of 35.64 (18 to 55) years. Pre-treatment DMS ranged from 6.5 to 57 mean (SD) 18.21 (13.38). At the end of the study, DMS ranged from 0 to 15 mean (SD) 3.14 (3.86). Statistical analysis of the differences between pre-treatment and post-treatment DMS showed a significant decrease in DMS at the end of the treatment period (p = 0.0001). Regarding the disability scale, the pre-treatment disability scale ranged from 7 to 18 mean (SD) 9.46 (3.02). At the end of the study, DMS ranged from 0 to 3 mean (SD) 1.46 (1.13). There was a statistically highly significant decrease in the Disability Scale at the end of the treatment period (p-value 0.0001). This study suggests that the HTS can be considered an effective treatment modality for dystonia, as it significantly decreases both the DMS and the Disability scale.

Keywords: HTS, dystonia, DMS, disability scale

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Authors: M. Taouzari, A. Sardi, J. El Aoufi, Ahmed Mouhsen

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The purpose of this work is to design a reader antenna fed by 90° hybrid coupler that would ensure a tag which is detected regardless of its orientation for the radio frequency identification system covering the UHF and ISM bands frequencies. Based on this idea, the proposed work is dividing in two parts, first part is about study and design hybrid coupler using the resonators planar called T-and Pi networks operating in commercial bands. In the second part, the proposed antenna fed by the hybrid coupler is designed on FR4 substrate with dielectric permittivity 4.4, thickness dielectric 1.6mm and loss tangent 0.025. The T-slot is inserted in patch of the proposed antenna fed by the hybrid coupler is first designed, optimized and simulated using electromagnetic simulator ADS and then simulated in a full wave simulation software CST Microwave Studio. The simulated antenna by the both softwares achieves the expected performances in terms of matching, pattern radiation, phase shifting, gain and size.

Keywords: dual band antenna, RFID, hybrid coupler, polarization, radiation pattern

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Authors: Buddhi Arachchige, Hessam Ghasemnejad

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In this study, the post impact behavior of curved composite plates subjected to low velocity impact was studied analytically and numerically. Approaches to damage modelling are proposed through the degradation of stiffness in the damaged region by reduction of thickness in the damage region. Spring-mass models were used to model the impact response of the plate and impactor. The study involved designing two damage models to compare and contrast the model best fitted with the numerical results. The theoretical force-time responses were compared with the numerical results obtained through a detailed study carried out in LS-DYNA. The modified damage model established a good prediction with the analytical force-time response for different layups and geometry. This study provides a gateway in selecting the most effective layups for variable stiffness curved composite panels able to withstand a higher impact damage.

Keywords: analytical modelling, composite damage, impact, variable stiffness

Procedia PDF Downloads 279

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

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Authors: Pengfei Liu, Yiyi Xu

Abstract:

There have been substantial incidents of wind turbine blade fractures and failures due to the lack of systematic blade strength design method incorporated with the aerodynamic forces and power generation efficiency. This research was to develop a methodology and procedure for the wind turbine rotor blade strength taking into account the strength, integration, and aerodynamic performance in terms of power generation efficiency. The wind turbine blade designed using this method and procedure will have a uniform strength across the span to save unnecessary thickness in many blade radial locations and yet to maintain the optimum power generation performance. A turbine rotor code, taking into account both aerodynamic and structural properties, was developed. An existing wind turbine blade was used as an example. For a condition of extreme wind speed of 100 km per hour, the design reduced about 19% of material usage while maintaining the optimum power regeneration efficiency.

Keywords: renewable energy, wind turbine, turbine blade strength, aerodynamics-strength coupled optimization

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Authors: Jinjun Jiang, Lianzhong Chen, Rui Xu

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The accurate of model attitude angel plays an important role on the aerodynamic test results in the wind tunnel test. The original method applies the spherical coordinate system transformation to obtain attitude angel calculation.The model attitude angel is obtained by coordinate transformation and spherical surface mapping applying the nominal attitude angel (the balance attitude angel in the wind tunnel coordinate system) indicated by the mechanism. First, the coordinate transformation of this method is not only complex but also difficult to establish the transformed relationship between the space coordinate systems especially after many steps of coordinate transformation, moreover it cannot realize the iterative calculation of the interference relationship between attitude angels; Second, during the calculate process to solve the problem the arc is approximately used to replace the straight line, the angel for the tangent value, and the inverse trigonometric function is applied. Therefore, in the calculation of attitude angel, the process is complex and inaccurate, which can be solved approximately when calculating small attack angel. However, with the advancing development of modern aerodynamic unsteady research, the aircraft tends to develop high or super large attack angel and unsteadyresearch field.According to engineering practice and vector theory, the concept of vector angel coordinate systemis proposed for the first time, and the vector angel coordinate system of attitude angel is established.With the iterative correction calculation and avoiding the problem of approximate and inverse trigonometric function solution, the model attitude calculation process is carried out in detail, which validates that the calculation accuracy and accuracy of model attitude angels are improved.Based on engineering and theoretical methods, a vector angel coordinate systemis established for the first time, which gives the transformation and angel definition relations between different flight attitude coordinate systems, that can accurately calculate the attitude angel of the corresponding coordinate systemand determine its direction, especially in the channel coupling calculation, the calculation of the attitude angel between the coordinate systems is only related to the angel, and has nothing to do with the change order s of the coordinate system, whichsimplifies the calculation process.

Keywords: attitude angel, angel vector coordinate system, iterative calculation, spherical coordinate system, wind tunnel test

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Authors: Harche Rima, Laoufi Nadia Aicha

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This work focuses on the study and modeling of the fouling phenomenon in a vertical pipe. In the first step, milk is one of the fluids obeying the phenomenon of fouling because of the denaturation of these proteins, especially lactoglobulin, which is the active element of milk, and to facilitate its use, we chose to study milk as a fouling fluid. In another step, we consider the test section of our installation as a tubular-type heat exchanger that works against the current and in a closed circuit. A simple mathematical model of Kern & Seaton, based on the kinetics of the fouling resistance, was used to evaluate the influence of the operating parameters (fluid flow velocity and exchange wall temperature) on the fouling resistance. The influence of the variation of the fouling resistance with the operating conditions on the efficiency of the heat exchanger and the importance of the dirty state exchange coefficient as an exchange quality control parameter were discussed and examined. On the other hand, an electronic scanning microscope analysis was performed on the milk deposit in order to obtain its actual image and composition, which allowed us to calculate the thickness of this deposit.

Keywords: fouling, milk, tubular heat exchanger, fouling resistance

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

Procedia PDF Downloads 300

Authors: Mohamed El Horri, Amine Mouden, Reda Messaoudi, Mohamed Chekkal, Driss Benlaldj, Malika Baghdadi, Lahcene Benmahdi, Fatima Seghier

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Background/aim: Recently, the Von Willebrand factor antigen (vWF-Ag)has been identified as a new marker of portal hypertension (PH) and its complications. Few studies talked about its role in the prediction of esophageal varices. VWF-Ag is considered a non-invasive approach, In order to avoid the endoscopic burden, cost, drawbacks, unpleasant and repeated examinations to the patients. In our study, we aimed to evaluate the ability of this marker in the prediction of another complication of portal hypertension, which is portal hypertensive gastropathy (PHG), the one that is diagnosed also by endoscopic tools. Patients and methods: It is about a prospective study, which include 124 cirrhotic patients with no history of bleeding who underwent screening endoscopy for PH-related complications like esophageal varices (EVs) and PHG. Routine biological tests were performed as well as the VWF-Ag testing by both ELFA and Immunoturbidimetric techniques. The diagnostic performance of our marker was assessed using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic curves. Results: 124 patients were enrolled in this study, with a mean age of 58 years [CI: 55 – 60 years] and a sex ratio of 1.17. Viral etiologies were found in 50% of patients. Screening endoscopy revealed the presence of PHG in 20.2% of cases, while for EVsthey were found in 83.1% of cases. VWF-Ag levels, were significantly increased in patients with PHG compared to those who have not: 441% [CI: 375 – 506], versus 279% [CI: 253 – 304], respectively (p <0.0001). Using the area under the receiver operating characteristic curve (AUC), vWF-Ag was a good predictor for the presence of PHG. With a value higher than 320% and an AUC of 0.824, VWF-Ag had an 84% sensitivity, 74% specificity, 44.7% positive predictive value, 94.8% negative predictive value, and 75.8% diagnostic accuracy. Conclusion: VWF-Ag is a good non-invasive low coast marker for excluding the presence of PHG in patients with liver cirrhosis. Using this marker as part of a selective screening strategy might reduce the need for endoscopic screening and the coast of the management of these kinds of patients.

Keywords: von willebrand factor, portal hypertensive gastropathy, prediction, liver cirrhosis

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Hazem A. Abdelfattah, Salia H. Khafaji

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Apparel industry needs to direct scientific researches to develop it , and because of the importance of a men’s suit jacket industry, the study of the basics of men’s jacket pattern making requires a high degree of accuracy and efficiency which contain a lot of technical and skill aspects to give the jacket a drape, comfort and good fitting , prompting researchers to think about the use of men’s mannequin with sizes (M-L-XL) to devise a method to draft a paper pattern for the men's suit jacket to use it in the industry easily and quickly and achieve the required good fitting.

Keywords: draping, pattern, men, jacket

Procedia PDF Downloads 353

Authors: Wenfa Yu, Thuva Gnanasampanthan, John Finlay, Jessica Clarke, Charlotte Anderson, Tony Clare, Axel Rosenhahn

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Marine biofouling is a worldwide problem at vast economic and ecological costs. Historically it was combated with toxic coatings such as tributyltin. As those coatings being banned nowadays, finding environmental friendly antifouling solution has become an urgent topic. In this study antifouling coatings consisted of natural occurring polysaccharides hyaluronic acid (HA), alginic acid (AA), chitosan (Ch) and polyelectrolyte polyethylenimine (PEI) are constructed into polyelectrolyte multilayers (PEMs) in a Layer-by-Layer (LbL) method. LbL PEM construction is a straightforward way to assemble biomacromolecular coatings on surfaces. Advantages about PEM include ease of handling, highly diverse PEM composition, precise control over the thickness and so on. PEMs have been widely employed in medical application and there are numerous studies regarding their protein adsorption, elasticity and cell adhesive properties. With the adjustment of coating composition, termination layer charge, coating morphology and cross-linking method, it is possible to prepare low marine biofouling coatings with PEMs. In this study, using spin coating technology, PEM construction was achieved at smooth multilayers with roughness as low as 2nm rms and highly reproducible thickness around 50nm. To obtain stability in sea water, the multilayers were covalently cross-linked either thermally or chemically. The cross-linking method affected surface energy, which was reflected in water contact angle, thermal cross-linking led to hydrophobic surfaces and chemical cross-linking generated hydrophilic surfaces. The coatings were then evaluated regarding its protein resistance and biological species resistance. While the hydrophobic thermally cross-linked PEM had low resistance towards proteins, the resistance of chemically cross-linked PEM strongly depended on the PEM termination layer and the charge of the protein, opposite charge caused high adsorption and same charge low adsorption, indicating electrostatic interaction plays a crucial role in the protein adsorption processes. Ulva linza was chosen as the biological species for antifouling performance evaluation. Despite of the poor resistance towards protein adsorption, thermally cross-linked PEM showed good resistance against Ulva spores settlement, the chemically cross-linked multilayers showed poor resistance regardless of the termination layer. Marine species adhesion is a complex process, although it involves proteins as bioadhesives, protein resistance its own is not a fully indicator for its antifouling performance. The species will pre select the surface, responding to cues like surface energy, chemistry, or charge and so on. Thus making it difficult for one single factors to determine its antifouling performance. Preparing PEM coating is a comprehensive work involving choosing polyelectrolyte combination, determining termination layer and the method for cross-linking. These decisions will affect PEM properties such as surface energy, charge, which is crucial, since biofouling is a process responding to surface properties in a highly sensitive and dynamic way.

Keywords: hyaluronic acid, polyelectrolyte multilayers, protein resistance, Ulva linza zoospores

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Authors: H. Farokhi, A. Bahadoran

Abstract:

This paper is focused on the absorbance and magnetic properties of a novel nanocomposite based on conducting polymer, carbon black and barium hexaferrite in epoxy resin on the E-glass fibre substrate. The highly conductive nanocomposite was provided by in-situ polymerization of aniline in the presence of carbon black (C) and barium hexaferrite (BaFe12O19) as electromagnetic absorbance material. The structure, morphology, and magnetic properties of samples were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM). SEM images showed the uniformly coated PAni on the surface of carbon black and barium hexaferrite. XRD peaks also verified the presence of carbon black and barium hexaferrite in the nanocomposite. The microwave characteristics determined from the magnetic and dielectric properties of the elastomeric composites obtained from scattering data by fitting the samples in a waveguide, where measured in the frequency in X-band frequency range, the range of 8 to 12 GHz. The reflection losses were evaluated to be less than −5dB over the whole X-band frequency (8–12 GHz) for the thickness of 1.4mm.

Keywords: conductive polymer, magnetic materials, capacitance, electrochemical cell

Procedia PDF Downloads 250