Search results for: EEG–signal processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4961

Search results for: EEG–signal processing

2531 The Evaluation of Current Pile Driving Prediction Methods for Driven Monopile Foundations in London Clay

Authors: John Davidson, Matteo Castelletti, Ismael Torres, Victor Terente, Jamie Irvine, Sylvie Raymackers

Abstract:

The current industry approach to pile driving predictions consists of developing a model of the hammer-pile-soil system which simulates the relationship between soil resistance to driving (SRD) and blow counts (or pile penetration per blow). The SRD methods traditionally used are broadly based on static pile capacity calculations. The SRD is used in combination with the one-dimensional wave equation model to indicate the anticipated blowcounts with depth for specific hammer energy settings. This approach has predominantly been calibrated on relatively long slender piles used in the oil and gas industry but is now being extended to allow calculations to be undertaken for relatively short rigid large diameter monopile foundations. This paper evaluates the accuracy of current industry practice when applied to a site where large diameter monopiles were installed in predominantly stiff fissured clay. Actual geotechnical and pile installation data, including pile driving records and signal matching analysis (based upon pile driving monitoring techniques), were used for the assessment on the case study site.

Keywords: driven piles, fissured clay, London clay, monopiles, offshore foundations

Procedia PDF Downloads 220
2530 Effect of Hot Equal Channel Angular Pressing Process on Mechanical Properties of Commercial Pure Titanium

Authors: Seyed Ata Khalkhkali Sharifi, Gholamhossein Majzoubi, Farhad Abroush

Abstract:

Developing mechanical properties of pure titanium has been reviewed in this paper by using ECAP process. At the first step of this article, the experimental samples were prepared as mentioned in the standards. Then pure grade 2 Ti was processed via equal-channel angular pressing (ECAp) for 2 passes following route-A at 400°C. After processing, the microstructural evolution, tensile, fatigue, hardness properties and wear behavior were investigated. Finally, the effect of ECAP process on these samples was analyzed. The results showed improvement in strength values with a slight decrease in ductility. The analysis on 30 points within the sample showed hardness increase in each pass. Also, it was concluded that fatigue properties were increased too.

Keywords: equal-channel angular pressing, titanium, mechanical behavior, engineering materials and applications

Procedia PDF Downloads 255
2529 CookIT: A Web Portal for the Preservation and Dissemination of Traditional Italian Recipes

Authors: M. T. Artese, G. Ciocca, I. Gagliardi

Abstract:

Food is a social and cultural aspect of every individual. Food products, processing, and traditions have been identified as cultural objects carrying history and identity of social groups. Traditional recipes are passed down from one generation to the other, often to strengthen the link with the territory. The paper presents CookIT, a web portal developed to collect Italian traditional recipes related to regional cuisine, with the purpose to disseminate the knowledge of typical Italian recipes and the Mediterranean diet which is a significant part of Italian cuisine. The system designed is completed with multimodal means of browsing and data retrieval. Stored recipes can be retrieved integrating and combining a number of different methods and keys, while the results are displayed using classical styles, such as list and mosaic, and also using maps and graphs, with which users can play using available keys for interaction.

Keywords: collaborative portal, Italian cuisine, intangible cultural heritage, traditional recipes, searching and browsing

Procedia PDF Downloads 148
2528 The Effect of Precipitation on Weed Infestation of Spring Barley under Different Tillage Conditions

Authors: J. Winkler, S. Chovancová

Abstract:

The article deals with the relation between rainfall in selected months and subsequent weed infestation of spring barley. The field experiment was performed at Mendel University agricultural enterprise in Žabčice, Czech Republic. Weed infestation was measured in spring barley vegetation in years 2004 to 2012. Barley was grown in three tillage variants: conventional tillage technology (CT), minimization tillage technology (MT), and no tillage (NT). Precipitation was recorded in one-day intervals. Monthly precipitation was calculated from the measured values in the months of October through to April. The technique of canonical correspondence analysis was applied for further statistical processing. 41 different species of weeds were found in the course of the 9-year monitoring period. The results clearly show that precipitation affects the incidence of most weed species in the selected months, but acts differently in the monitored variants of tillage technologies.

Keywords: weeds, precipitation, tillage, weed infestation forecast

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2527 Rule-Based Expert System for Headache Diagnosis and Medication Recommendation

Authors: Noura Al-Ajmi, Mohammed A. Almulla

Abstract:

With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

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2526 Ontological Modeling Approach for Statistical Databases Publication in Linked Open Data

Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

Abstract:

At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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2525 Design and Optimization for a Compliant Gripper with Force Regulation Mechanism

Authors: Nhat Linh Ho, Thanh-Phong Dao, Shyh-Chour Huang, Hieu Giang Le

Abstract:

This paper presents a design and optimization for a compliant gripper. The gripper is constructed based on the concept of compliant mechanism with flexure hinge. A passive force regulation mechanism is presented to control the grasping force a micro-sized object instead of using a sensor force. The force regulation mechanism is designed using the planar springs. The gripper is expected to obtain a large range of displacement to handle various sized objects. First of all, the statics and dynamics of the gripper are investigated by using the finite element analysis in ANSYS software. And then, the design parameters of the gripper are optimized via Taguchi method. An orthogonal array L9 is used to establish an experimental matrix. Subsequently, the signal to noise ratio is analyzed to find the optimal solution. Finally, the response surface methodology is employed to model the relationship between the design parameters and the output displacement of the gripper. The design of experiment method is then used to analyze the sensitivity so as to determine the effect of each parameter on the displacement. The results showed that the compliant gripper can move with a large displacement of 213.51 mm and the force regulation mechanism is expected to be used for high precision positioning systems.

Keywords: flexure hinge, compliant mechanism, compliant gripper, force regulation mechanism, Taguchi method, response surface methodology, design of experiment

Procedia PDF Downloads 325
2524 Visualization of Wave Propagation in Monocoupled System with Effective Negative Stiffness, Effective Negative Mass, and Inertial Amplifier

Authors: Abhigna Bhatt, Arnab Banerjee

Abstract:

A periodic system with only a single coupling degree of freedom is called a monocoupled system. Monocoupled systems with mechanisms like mass in the mass system generates effective negative mass, mass connected with rigid links generates inertial amplification, and spring-mass connected with a rigid link generateseffective negative stiffness. In this paper, the representative unit cell is introduced, considering all three mechanisms combined. Further, the dynamic stiffness matrix of the unit cell is constructed, and the dispersion relation is obtained by applying the Bloch theorem. The frequency response function is also calculated for the finite length of periodic unit cells. Moreover, the input displacement signal is given to the finite length of periodic structure and using inverse Fourier transform to visualize the wave propagation in the time domain. This visualization explains the sudden attenuation in metamaterial due to energy dissipation by an embedded resonator at the resonance frequency. The visualization created for wave propagation is found necessary to understand the insights of physics behind the attenuation characteristics of the system.

Keywords: mono coupled system, negative effective mass, negative effective stiffness, inertial amplifier, fourier transform

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2523 Technology Computer Aided Design Simulation of Space Charge Limited Conduction in Polycrystalline Thin Films

Authors: Kunj Parikh, S. Bhattacharya, V. Natarajan

Abstract:

TCAD numerical simulation is one of the most tried and tested powerful tools for designing devices in semiconductor foundries worldwide. It has also been used to explain conduction in organic thin films where the processing temperature is often enough to make homogeneous samples (often imperfect, but homogeneously imperfect). In this report, we have presented the results of TCAD simulation in multi-grain thin films. The work has addressed the inhomogeneity in one dimension, but can easily be extended to two and three dimensions. The effect of grain boundaries has mainly been approximated as barriers located at the junction between two adjacent grains. The effect of the value of grain boundary barrier, the bulk traps, and the measurement temperature have been investigated.

Keywords: polycrystalline thin films, space charge limited conduction, Technology Computer-Aided Design (TCAD) simulation, traps

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2522 Processing of Flexible Dielectric Nanocomposites Using Nanocellulose and Recycled Alum Sludge for Wearable Technology Applications

Authors: D. Sun, L. Saw, A. Onyianta, D. O’Rourke, Z. Lu, C. See, C. Wilson, C. Popescu, M. Dorris

Abstract:

With the rapid development of wearable technology (e.g., smartwatch, activity trackers and health monitor devices), flexible dielectric materials with environmental-friendly, low-cost and high-energy efficiency characteristics are in increasing demand. In this work, a flexible dielectric nanocomposite was processed by incorporating two components: cellulose nanofibrils and alum sludge in a polymer matrix. The two components were used in the reinforcement phase as well as for enhancing the dielectric properties; they were processed using waste materials that would otherwise be disposed to landfills. Alum sludge is a by-product of the water treatment process in which aluminum sulfate is prevalently used as the primary coagulant. According to the data from a project partner-Scottish Water: there are approximately 10k tons of alum sludge generated as a waste from the water treatment work to be landfilled every year in Scotland. The industry has been facing escalating financial and environmental pressure to develop more sustainable strategies to deal with alum sludge wastes. In the available literature, some work on reusing alum sludge has been reported (e.g., aluminum recovery or agriculture and land reclamation). However, little work can be found in applying it to processing energy materials (e.g., dielectrics) for enhanced energy density and efficiency. The alum sludge was collected directly from a water treatment plant of Scottish Water and heat-treated and refined before being used in preparing composites. Cellulose nanofibrils were derived from water hyacinth, an invasive aquatic weed that causes significant ecological issues in tropical regions. The harvested water hyacinth was dried and processed using a cost-effective method, including a chemical extraction followed by a homogenization process in order to extract cellulose nanofibrils. Biodegradable elastomer polydimethylsiloxane (PDMS) was used as the polymer matrix and the nanocomposites were processed by casting raw materials in Petri dishes. The processed composites were characterized using various methods, including scanning electron microscopy (SEM), rheological analysis, thermogravimetric and X-ray diffraction analysis. The SEM result showed that cellulose nanofibrils of approximately 20nm in diameter and 100nm in length were obtained and the alum sludge particles were of approximately 200um in diameters. The TGA/DSC analysis result showed that a weight loss of up to 48% can be seen in the raw material of alum sludge and its crystallization process has been started at approximately 800°C. This observation coincides with the XRD result. Other experiments also showed that the composites exhibit comprehensive mechanical and dielectric performances. This work depicts that it is a sustainable practice of reusing such waste materials in preparing flexible, lightweight and miniature dielectric materials for wearable technology applications.

Keywords: cellulose, biodegradable, sustainable, alum sludge, nanocomposite, wearable technology, dielectric

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2521 Comparison of Different Extraction Methods for the Determination of Polyphenols

Authors: Senem Suna

Abstract:

Extraction of bioactive compounds from several food/food products comes as an important topic and new trend related with health promoting effects. As a result of the increasing interest in natural foods, different methods are used for the acquisition of these components especially polyphenols. However, special attention has to be paid to the selection of proper techniques or several processing technologies (supercritical fluid extraction, microwave-assisted extraction, ultrasound-assisted extraction, powdered extracts production) for each kind of food to get maximum benefit as well as the obtainment of phenolic compounds. In order to meet consumer’s demand for healthy food and the management of quality and safety requirements, advanced research and development are needed. In this review, advantages, and disadvantages of different extraction methods, their opportunities to be used in food industry and the effects of polyphenols are mentioned in details. Consequently, with the evaluation of the results of several studies, the selection of the most suitable food specific method was aimed.

Keywords: bioactives, extraction, powdered extracts, supercritical fluid extraction

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2520 Developing Biocompatible Iridium Oxide Electrodes for Bone-Guided Extra-Cochlear Implant

Authors: Yung-Shan Lu, Chia-Fone Lee, Shang-Hsuan Li, Chien-Hao Liu

Abstract:

Recently, various bioelectronic devices have been developed for neurologic disease treatments via electro-stimulations such as cochlear implants and retinal prosthesis. Since the electric signal needs electrodes to be transmitted to an organism, electrodes play an important role of stimulations. The materials of stimulation electrodes affect the efficiency of the delivered currents. The higher the efficiency of the electrodes, the lower the threshold current can be used to stimulate the organism which minimizes the potential damages to the adjacent tissues. In this study, we proposed a biocompatible composite electrode composed of high-charge-capacity iridium oxide (IrOₓ) film for a bone-guide extra-cochlear implant. IrOₓ was exploited to decrease the threshold current due to its high capacitance and low impedance. The IrOₓ electrode was fabricated via microelectromechanical systems (MEMS) photolithography and examined with in-vivo tests with guinea pigs. Based on the measured responses of brain waves to sound, the results demonstrated that IrOₓ electrodes have a lower threshold current compared with the Platinum (Pt) electrodes. The research results are expected to be beneficial for implantable and biocompatible electrodes for electrical stimulations.

Keywords: cochlear implants, electrode, electrical stimulation, iridium oxide

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2519 Enhancing Patch Time Series Transformer with Wavelet Transform for Improved Stock Prediction

Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

Abstract:

Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

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2518 Mathematical Modelling of Bacterial Growth in Products of Animal Origin in Storage and Transport: Effects of Temperature, Use of Bacteriocins and pH Level

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

Abstract:

The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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2517 Contrast Enhancement of Masses in Mammograms Using Multiscale Morphology

Authors: Amit Kamra, V. K. Jain, Pragya

Abstract:

Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other state-of-the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Keywords: enhancement, mammography, multi-scale, mathematical morphology

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2516 Selection of Wind Farms to Add Virtual Inertia Control to Assist the Power System Frequency Regulation

Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

Abstract:

Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

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2515 Searching Linguistic Synonyms through Parts of Speech Tagging

Authors: Faiza Hussain, Usman Qamar

Abstract:

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

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

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2514 Mathematical Modeling of Carotenoids and Polyphenols Content of Faba Beans (Vicia faba L.) during Microwave Treatments

Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

Abstract:

Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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2513 Fused Structure and Texture (FST) Features for Improved Pedestrian Detection

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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2512 Development of Ferrous-Aluminum Alloys from Recyclable Material by High Energy Milling

Authors: Arnold S. Freitas Neto, Rodrigo E. Coelho, Erick S. Mendonça

Abstract:

This study aimed to obtain an alloy of Iron and Aluminum in the proportion of 50% of atomicity for each constituent. Alloys were obtained by processing recycled aluminum and chips of 1200 series carbon steel in a high-energy mill. For the experiment, raw materials were processed thorough high energy milling before mixing the substances. Subsequently, the mixture of 1200 series carbon steel and Aluminum powder was carried out a milling process. Thereafter, hot compression was performed in a closed die in order to obtain the samples. The pieces underwent heat treatments, sintering and aging. Lastly, the composition and the mechanical properties of their hardness were analyzed. In this paper, results are compared with previous studies, which used iron powder of high purity instead of Carbon steel in the composition.

Keywords: Fe-Al alloys, high energy milling, metallography characterization, powder metallurgy

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2511 Hit-Or-Miss Transform as a Tool for Similar Shape Detection

Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

Abstract:

This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: hit-or-miss operator transform, HMT, binary morphological operation, shape detection, binary images processing

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2510 A Custom Convolutional Neural Network with Hue, Saturation, Value Color for Malaria Classification

Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

Abstract:

Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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2509 Human Posture Estimation Based on Multiple Viewpoints

Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

Abstract:

This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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2508 Computational Analysis on Thermal Performance of Chip Package in Electro-Optical Device

Authors: Long Kim Vu

Abstract:

The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

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2507 Post Growth Annealing Effect on Deep Level Emission and Raman Spectra of Hydrothermally Grown ZnO Nanorods Assisted by KMnO4

Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

Abstract:

Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

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2506 Precise Determination of the Residual Stress Gradient in Composite Laminates Using a Configurable Numerical-Experimental Coupling Based on the Incremental Hole Drilling Method

Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

Abstract:

Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

Procedia PDF Downloads 129
2505 Offset Dependent Uniform Delay Mathematical Optimization Model for Signalized Traffic Network Using Differential Evolution Algorithm

Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

Abstract:

A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

Procedia PDF Downloads 272
2504 Level Set and Morphological Operation Techniques in Application of Dental Image Segmentation

Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

Abstract:

Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

Procedia PDF Downloads 312
2503 Long Memory and ARFIMA Modelling: The Case of CPI Inflation for Ghana and South Africa

Authors: A. Boateng, La Gil-Alana, M. Lesaoana; Hj. Siweya, A. Belete

Abstract:

This study examines long memory or long-range dependence in the CPI inflation rates of Ghana and South Africa using Whittle methods and autoregressive fractionally integrated moving average (ARFIMA) models. Standard I(0)/I(1) methods such as Augmented Dickey-Fuller (ADF), Philips-Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests were also employed. Our findings indicate that long memory exists in the CPI inflation rates of both countries. After processing fractional differencing and determining the short memory components, the models were specified as ARFIMA (4,0.35,2) and ARFIMA (3,0.49,3) respectively for Ghana and South Africa. Consequently, the CPI inflation rates of both countries are fractionally integrated and mean reverting. The implication of this result will assist in policy formulation and identification of inflationary pressures in an economy.

Keywords: Consumer Price Index (CPI) inflation rates, Whittle method, long memory, ARFIMA model

Procedia PDF Downloads 364
2502 Tamper Resistance Evaluation Tests with Noise Resources

Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

Abstract:

Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

Procedia PDF Downloads 497