Search results for: Stability and accuracy

Authors: N. Abbas, S. Lagomarsino, S. Cattari

Abstract:

Examining existing experimental results for shallow rigid foundations subjected to vertical centric load (N), accompanied or not with a bending moment (M), two main non-linear mechanisms governing the cyclic response of the soil-foundation system can be distinguished: foundation uplift and soil yielding. A soil-foundation failure limit, is defined as a domain of resistance in the two dimensional (2D) load space (N, M) inside of which lie all the admissible combinations of loads; these latter correspond to a pure elastic, non-linear elastic or plastic behavior of the soil-foundation system, while the points lying on the failure limit correspond to a combination of loads leading to a failure of the soil-foundation system. In this study, the proposed resistance domain is constructed analytically based on mechanics. Original elastic limit, uplift initiation limit and iso-uplift limits are constructed inside this domain. These limits give a prediction of the mechanisms activated for each combination of loads applied to the foundation. A comparison of the proposed failure limit with experimental tests existing in the literature shows interesting results. Also, the developed uplift initiation limit and iso-uplift curves are confronted with others already proposed in the literature and widely used due to the absence of other alternatives, and remarkable differences are noted, showing evident errors in the past proposals and relevant accuracy for those given in the present work.

Keywords: Foundation uplift, Iso-uplift curves, Resistance domain, Soil yield.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2171

Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

Abstract:

This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1625

Authors: Obinna K. Ihesiulor, Krishna Shankar, Paul Smith, Alan Fien

Abstract:

Excessive fretting wear at the taper-trunnion junction (trunnionosis) apparently contributes to the high failure rates of hip implants. Implant wear and corrosion lead to the release of metal particulate debris and subsequent release of metal ions at the tapertrunnion surface. This results in a type of metal poisoning referred to as metallosis. The consequences of metal poisoning include; osteolysis (bone loss), osteoarthritis (pain), aseptic loosening of the prosthesis and revision surgery. Follow up after revision surgery, metal debris particles are commonly found in numerous locations. Background: A stable connection between the femoral ball head (taper) and stem (trunnion) is necessary to prevent relative motions and corrosion at the taper junction. Hence, the importance of component assembly cannot be over-emphasized. Therefore, the aim of this study is to determine the influence of head-stem junction assembly by press fitting and the subsequent disengagement/disassembly on the connection strength between the taper ball head and stem. Methods: CoCr femoral heads were assembled with High stainless hydrogen steel stem (trunnion) by Push-in i.e. press fit; and disengaged by pull-out test. The strength and stability of the two connections were evaluated by measuring the head pull-out forces according to ISO 7206-10 standards. Findings: The head-stem junction strength linearly increases with assembly forces.

Keywords: Wear, modular hip prosthesis, taper head-stem, force assembly, force disassembly.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2452

Authors: Sambit Prasad Kar, P.Palanisamy

Abstract:

In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.

Keywords: Frequency estimation, peak search, subspace-based method without eigen decomposition, quadratic convex function.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1730

Authors: Parvinder S. Sandhu, Sandeep Khimta, Kiranpreet Kaur

Abstract:

The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Keywords: Growing Neural Gas, data clustering, fault prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1864

Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

Abstract:

Unmanned Surface Vehicles (USVs) hold significant value for their capacity to undertake hazardous and labor-intensive operations over aquatic environments. Object detection tasks are significant in these applications. Nonetheless, the efficacy of USVs in object detection is impeded by several intrinsic challenges, including the intricate dispersal of obstacles, reflections emanating from coastal structures, and the presence of fog over water surfaces, among others. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. The MMW radar is a complementary tool to vision sensors, offering reliable environmental data. This approach involves the conversion of the radar’s 3D point cloud into a 2D radar pseudo-image, thereby standardizing the format for radar and vision data by leveraging a point transformer. Furthermore, this paper proposes the development of a multi-source object detection network, named RV-YOLOX, which leverages radar-vision integration specifically tailored for inland waterway environments. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: Inland waterways, object detection, YOLO, sensor fusion, self-attention, deep learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 289

Authors: S. Visetpotjanakit, C. Khrautongkieo

Abstract:

Radiation monitoring in the environment and foodstuffs is one of the main responsibilities of Office of Atoms for Peace (OAP) as the nuclear regulatory body of Thailand. The main goal of the OAP is to assure the safety of the Thai people and environment from any radiological incidents. Various radioanalytical methods have been developed to monitor radiation and radionuclides in the environmental and foodstuff samples. To validate our analytical performance, several proficiency test exercises from the International Atomic Energy Agency (IAEA) have been performed. Here, the results of a proficiency test exercise referred to as the Proficiency Test for Tritium, Cobalt, Strontium and Caesium Isotopes in Seawater 2017 (IAEA-RML-2017-01) are presented. All radionuclides excepting ³H were analysed using various radioanalytical methods, i.e. direct gamma-ray counting for determining ⁶⁰Co, ¹³⁴Cs and ¹³⁷Cs and developed radiochemical techniques for analysing ¹³⁴Cs, ¹³⁷Cs using AMP pre-concentration technique and 90Sr using di-(2-ethylhexyl) phosphoric acid (HDEHP) liquid extraction technique. The analysis results were submitted to IAEA. All results passed IAEA criteria, i.e. accuracy, precision and trueness and obtained ‘Accepted’ statuses. These confirm the data quality from the OAP environmental radiation laboratory to monitor radiation in the environment.

Keywords: International atomic energy agency, proficiency test, radiation monitoring, seawater.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 821

Authors: Lavanya Annadi, Fahimeh Jafari

Abstract:

Transportation brings immense benefits to society, but it also has its costs. Costs include the cost of infrastructure, personnel, and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion, and various indirect costs in terms of air transport. This research aims to predict the probabilistic crash prediction of vehicles using Machine Learning due to natural and structural reasons by excluding spontaneous reasons, like overspeeding, etc., in the United States. These factors range from meteorological elements such as weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity, to human-made structures, like road structure components such as Bumps, Roundabouts, No Exit, Turning Loops, Give Away, etc. The probabilities are categorized into ten distinct classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes in all states collected by the US government. The probability of the crash was determined by employing Multinomial Expected Value, and a classification label was assigned accordingly. We applied three classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-depth insights through exploratory data analysis.

Keywords: Road safety, crash prediction, exploratory analysis, machine learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 80

Authors: Wernhuar Tarng, Yuan-Yuan Chen, Chien-Lung Li, Kun-Rong Hsie, Mingteh Chen

Abstract:

An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Keywords: Smart phones, emotional speech recognition, socialnetworks, support vector machines, time-frequency parameter, Mel-scale frequency cepstral coefficients (MFCC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1841

Authors: Ashok Kumar, Vinod Kumar

Abstract:

Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2631

Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: Data fusion, Gaussian process regression, signal denoise, temporal extrapolation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 500

Authors: Somya Poonaya, Chawalit Thinvongpituk, Umphisak Teeboonma

Abstract:

Circular tubes have been widely used as structural members in engineering application. Therefore, its collapse behavior has been studied for many decades, focusing on its energy absorption characteristics. In order to predict the collapse behavior of members, one could rely on the use of finite element codes or experiments. These tools are helpful and high accuracy but costly and require extensive running time. Therefore, an approximating model of tubes collapse mechanism is an alternative for early step of design. This paper is also aimed to develop a closed-form solution of thin-walled circular tube subjected to bending. It has extended the Elchalakani et al.-s model (Int. J. Mech. Sci.2002; 44:1117-1143) to include the rate of energy dissipation of rolling hinge in the circumferential direction. The 3-D geometrical collapse mechanism was analyzed by adding the oblique hinge lines along the longitudinal tube within the length of plastically deforming zone. The model was based on the principal of energy rate conservation. Therefore, the rates of internal energy dissipation were calculated for each hinge lines which are defined in term of velocity field. Inextensional deformation and perfect plastic material behavior was assumed in the derivation of deformation energy rate. The analytical result was compared with experimental result. The experiment was conducted with a number of tubes having various D/t ratios. Good agreement between analytical and experiment was achieved.

Keywords: Bending, Circular tube, Energy, Mechanism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3509

Authors: Mohammad Reza Mohammadian, Dariush Sattarzadeh, Mir Mohammad Javad Poor Hadi Hosseini

Abstract:

Population growth, urban development and urban buildup have disturbed the balance between the nature and the city, and so leading to the loss of quality of sustainability of proximity to rivers. While in the past, the sides of urban rivers were considered as urban green space. Urban rivers and their sides that have environmental, social and economic values are important to achieve sustainable development. So far, efforts have been made at various scales in various cities around the world to revitalize these areas. On the other hand, biophilic design is an innovative design approach in which attention to natural details and relation to nature is a fundamental concept. The purpose of this study is to provide an integrated framework of urban design using the potential of urban rivers (in order to increase sustainability) with a biophilic design approach to be used in cities in developing countries. The methodology of the research is based on the collection of data and information from research and projects including a study on biophilic design, investigations and projects related to the urban rivers, and a review of the literature on sustainable urban development. Then studying the boundary of urban rivers is completed by examining case samples. Eventually, integrated framework of urban design, to design the boundaries of urban rivers in the cities of developing countries is presented regarding the factors affecting the design of these areas. The result shows that according to this framework, the potential of the river banks is utilized to increase not only the environmental sustainability but also social, economic and physical stability with regard to water, light, and the usage of indigenous materials, etc.

Keywords: Urban rivers, biophilic design, urban sustainability, nature.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1271

Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2003

Authors: Vishnu Raj, Chockalingam Prathap

Abstract:

The objective of this study was to explore the impact of variation in the exit annular area on the local flow field features and the flame stability of an annular premixed swirl burner (unconfined) operated with a premixed n-butane air mixture at an equivalence ratio (Φ) = 1, 1 bar, and 300K. A swirl burner with an axial swirl generator having a swirl number of 1.5 was used. Three different burner heads were chosen to have the exit area increased from 100%, 160%, and 220% resulting in inner and outer diameters and cross-sectional areas as (1) 10 mm & 15 mm, 98 mm2 (2) 17.5 mm & 22.5 mm, 157 mm2 and (3) 25 mm & 30 mm, 216 mm2. The bulk velocity and Reynolds number based on the hydraulic diameter and unburned gas properties were kept constant at 12 m/s and 4000. (i) Planar Particle Image Velocimetry (PIV) with TiO2 seeding particles and (ii) CH* chemiluminescence was used to measure the velocity fields and reaction zones of the swirl flames at 5 Hz, respectively. Velocity fields and the jet spreading rates measured at the isothermal and reactive conditions revealed that the presence of a flame significantly altered the flow field in the radial direction due to the gas expansion. Important observations from the flame measurements were: the height and maximum width of the recirculation bubbles normalized by the hydraulic diameter, and the jet spreading angles for the flames for the three exit area cases were: (a) 4.52, 1.95, 34◦, (b) 6.78, 2.37, 26◦, and (c) 8.73, 2.32, 22◦. The lean blowout (LBO) was also measured, and the respective equivalence ratios were: 0.80, 0.92, and 0.82. LBO was relatively narrow for the 157 mm2 case. For this case, PIV measurements showed that Turbulent Kinetic Energy and turbulent intensity were relatively high compared to the other two cases, resulting in higher stretch rates and narrower LBO.

Keywords: Chemiluminescence, jet spreading rate, lean blow out, swirl flow.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 265

Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

Abstract:

Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of living tissues to mechanical loads is necessary for a wide range of developing fields such as prosthetics design or computerassisted surgical interventions. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically, growth is one of the main sources. Extracting body organ’s shapes from medical imaging does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is gravity since an organ grows under its influence from birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. This paper presents an original computational framework based on gradual growth to determine the residual stresses due to growth. To illustrate the method, we apply it to a finite element model of a healthy human face reconstructed from medical images. The distribution of residual stress in facial tissues is computed, which can overcome the effect of gravity and maintain tissues firmness. Our assumption is that tissue wrinkles caused by aging could be a consequence of decreasing residual stress and thus not counteracting gravity. Taking into account these stresses seems therefore extremely important in maxillofacial surgery. It would indeed help surgeons to estimate tissues changes after surgery.

Keywords: Finite element method, growth, residual stress, soft tissue.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1685

Authors: Mojiri M, Ghazi Khanloo Sani K, Moghim Beigi A

Abstract:

The aim of this study was to compare the sensitometric properties of commonly used radiographic films processed with chemical solutions in different workload hospitals. The effect of different processing conditions on induced densities on radiologic films was investigated. Two accessible double emulsions Fuji and Kodak films were exposed with 11-step wedge and processed with Champion and CPAC processing solutions. The mentioned films provided in both workloads centers, high and low. Our findings displays that the speed and contrast of Kodak filmscreen in both work load (high and low) is higher than Fuji filmscreen for both processing solutions. However there was significant differences in films contrast for both workloads when CPAC solution had been used (p=0.000 and 0.028). The results showed base plus fog density for Kodak film was lower than Fuji. Generally Champion processing solution caused more speed and contrast for investigated films in different conditions and there was significant differences in 95% confidence level between two used processing solutions (p=0.01). Low base plus fog density for Kodak films provide more visibility and accuracy and higher contrast results in using lower exposure factors to obtain better quality in resulting radiographs. In this study we found an economic advantages since Champion solution and Kodak film are used while it makes lower patient dose. Thus, in a radiologic facility any change in film processor/processing cycle or chemistry should be carefully investigated before radiological procedures of patients are acquired.

Keywords: Sensitometry, densitometry, Radiographic film, processing solution

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1626

Authors: Mohamed Fathy Heweage, Xiao Wen, Ayman Mokhtar, Ahmed Eldamarawy

Abstract:

In this paper, we are interested in modeling, simulation, and measurement of the laser spot position with a quadrant detector. We enhance detection and tracking of semi-laser weapon decoding system based on microcontroller. The system receives the reflected pulse through quadrant detector and processes the laser pulses through a processing circuit, a microcontroller decoding laser pulse reflected by the target. The seeker accuracy will be enhanced by the decoding system, the laser detection time based on the receiving pulses number is reduced, a gate is used to limit the laser pulse width. The model is implemented based on Pulse Repetition Frequency (PRF) technique with two microcontroller units (MCU). MCU1 generates laser pulses with different codes. MCU2 decodes the laser code and locks the system at the specific code. The codes EW selected based on the two selector switches. The system is implemented and tested in Proteus ISIS software. The implementation of the full position determination circuit with the detector is produced. General system for the spot position determination was performed with the laser PRF for incident radiation and the mechanical system for adjusting system at different angles. The system test results show that the system can detect the laser code with only three received pulses based on the narrow gate signal, and good agreement between simulation and measured system performance is obtained.

Keywords: 4-quadrant detector, pulse code detection, laser guided weapons, pulse repetition frequency, ATmega 32 microcontrollers.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1530

Authors: Avishek Chanda, Nam Kyeun Kim, Debes Bhattacharyya

Abstract:

The use of renewable substitutes in various semi-structural and structural applications has experienced an increase since the last few decades. Sandwich panels have been used for many decades, although research on understanding the effects of the core structures on the panels’ fire-reaction properties is limited. The current work investigates the fire-performance of a corrugated sandwich panel made from renewable, biodegradable, and sustainable material, plywood. The bench-scale fire testing apparatus, cone-calorimeter, was employed to evaluate the required fire-reaction properties of the sandwich core in a panel configuration, with three corrugated layers glued together with face-sheets under a heat irradiance of 50 kW/m². The study helped in documenting a unique heat release trend associated with the fire performance of the 3-layered corrugated sandwich panels and in understanding the structural stability of the samples in the event of a fire. Furthermore, the total peak heat release rate was observed to be around 421 kW/m², which is significantly low compared to many polymeric materials in the literature. The total smoke production was also perceived to be very limited compared to other structural materials, and the total heat release was also nominal. The time to ignition of 21.7 s further outlined the advantages of using the plywood component since polymeric composites, even with flame-retardant additives, tend to ignite faster. Overall, the corrugated plywood sandwich panels had significant fire-reaction properties and could have important structural applications. The possible use of structural panels made from bio-degradable material opens a new avenue for the use of similar structures in sandwich panel preparation.

Keywords: Corrugated sandwich panel, fire-reaction properties, plywood, renewable material.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 428

Authors: Jungho Choi, Youngwan Cho

Abstract:

This paper presents an algorithm for the recognition and tracking of moving objects, 1/10 scale model car is used to verify performance of the algorithm. Presented algorithm for the recognition and tracking of moving objects in the paper is as follows. SURF algorithm is merged with Lucas-Kanade algorithm. SURF algorithm has strong performance on contrast, size, rotation changes and it recognizes objects but it is slow due to many computational complexities. Processing speed of Lucas-Kanade algorithm is fast but the recognition of objects is impossible. Its optical flow compares the previous and current frames so that can track the movement of a pixel. The fusion algorithm is created in order to solve problems which occurred using the Kalman Filter to estimate the position and the accumulated error compensation algorithm was implemented. Kalman filter is used to create presented algorithm to complement problems that is occurred when fusion two algorithms. Kalman filter is used to estimate next location, compensate for the accumulated error. The resolution of the camera (Vision Sensor) is fixed to be 640x480. To verify the performance of the fusion algorithm, test is compared to SURF algorithm under three situations, driving straight, curve, and recognizing cars behind the obstacles. Situation similar to the actual is possible using a model vehicle. Proposed fusion algorithm showed superior performance and accuracy than the existing object recognition and tracking algorithms. We will improve the performance of the algorithm, so that you can experiment with the images of the actual road environment.

Keywords: SURF, Optical Flow Lucas-Kanade, Kalman Filter, object recognition, object tracking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2291

Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

Abstract:

Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2173

Authors: Nooshin La'l Mohamadi

Abstract:

Due to the fact that in the new century customers tend to express globally increasing demands, networks of interconnected businesses have been established in societies and the management of such networks seems to be a major key through gaining competitive advantages. Supply chain management encompasses such managerial activities. Within a supply chain, a critical role is played by quality. QFD is a widely-utilized tool which serves the purpose of not only bringing quality to the ultimate provision of products or service packages required by the end customer or the retailer, but it can also initiate us into a satisfactory relationship with our initial customer; that is the wholesaler. However, the wholesalers- cooperation is considerably based on the capabilities that are heavily dependent on their locations and existing circumstances. Therefore, it is undeniable that for all companies each wholesaler possesses a specific importance ratio which can heavily influence the figures calculated in the House of Quality in QFD. Moreover, due to the competitiveness of the marketplace today, it-s been widely recognized that consumers- expression of demands has been highly volatile in periods of production. Apparently, such instability and proneness to change has been very tangibly noticed and taking it into account during the analysis of HOQ is widely influential and doubtlessly required. For a more reliable outcome in such matters, this article demonstrates the application viability of Analytic Network Process for considering the wholesalers- reputation and simultaneously introduces a mortality coefficient for the reliability and stability of the consumers- expressed demands in course of time. Following to this, the paper provides further elaboration on the relevant contributory factors and approaches through the calculation of such coefficients. In the end, the article concludes that an empirical application is needed to achieve broader validity.

Keywords: Analytic Network Process, Quality Function Deployment, QFD flaws, Supply Chain Management

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1425

Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

Abstract:

Using membrane technology and modification of milk protein structural properties, a lactose free yogurt was developed. The functional, textural and structural properties of the sample were evaluated and compared with the commercial ones. Results showed that the modification of protein in high fat set yogurt resulted in 11.55%, 18%, 20.21% and 7.08% higher hardness, consistency, water holding capacity, and shininess values compared with the control one. Furthermore, these indices of modified low fat set yogurt were 21.40%, 25.41%, 28.15% & 10.58% higher than the control one, which could be related to the gel network microstructural properties in yogurt formulated with modified protein. In this way, in comparison with the control one, the index of linkage strength (A), the number of linkages (z), and time scale of linkages (λrel) of the high fat modified yogurt were 22.10%, 50.68%, 21.82% higher than the control one; whereas, the average linear distance between two adjacent crosslinks (ξ), was 16.77% lower than the control one. For low fat modified yogurt, A, z, λrel, and ξ indices were 34.30%, 61.70% and 42.60% higher and 19.20% lower than the control one, respectively. The shelf life of modified yogurt was extended to 10 weeks in the refrigerator, while, the control set yogurt had a 3 weeks shelf life. The acidity of high fat and low fat modified yogurts increased from 76 to 84 and 72 to 80 Dornic degrees during 10 weeks of storage, respectively, whereas for control high fat and low fat yogurts they increased from 82 to 122 and 77 to 112 Dornic degrees, respectively. This behavior could be due to the elimination of microorganism’s source of energy in modified yogurt. Furthermore, the calories of high fat and low fat lactose free yogurts were 25% and 40% lower than their control samples, respectively. Generally, results showed that the lactose free yogurt with modified protein, despite of 1% lower protein content than the control one, showed better functional properties, nutritional properties, network parameters, and shelf stability, which could be promising in the set yogurt industry.

Keywords: Lactose free, low calorie, network properties, protein modification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 270

Authors: Yi-Feng Su, Chia-Tseng Chen, Hsueh-Lung Liao

Abstract:

The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.

Keywords: Lane mark detection, lane departure warning (LDW), dynamic range of interesting (DROI), forward collision warning (FCW), adaptive front-lighting system (AFS).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2156

Authors: S. Boria

Abstract:

In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: Composite material, crashworthiness, finite element analysis, optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1128

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 608

Authors: Gordana Kordić, Petra Palić

Abstract:

The European countries that during the past two decades based their exchange rate regimes on currency board arrangement (CBA) are usually analysed from the perspective of corner solution choice’s stabilisation effects. There is an open discussion on the positive and negative background of a strict exchange rate regime choice, although it should be seen as part of the transition process towards the monetary union membership. The focus of the paper is on the Baltic countries that after two decades of a rigid exchange rate arrangement and strongly influenced by global crisis are finishing their path towards the euro zone. Besides the stabilising capacity, the CBA is highly vulnerable regime, with limited developing potential. The rigidity of the exchange rate (and monetary) system, despite the ensured credibility, do not leave enough (or any) space for the adjustment and/or active crisis management. Still, the Baltics are in a process of recovery, with fiscal consolidation measures combined with (painful and politically unpopular) measures of internal devaluation. Today, two of them (Estonia and Latvia) are members of euro zone, fulfilling their ultimate transition targets, but de facto exchanging one fixed regime with another. The paper analyses the challenges for the CBA in unstable environment since the fixed regimes rely on imported stability and are sensitive to external shocks. With limited monetary instruments, these countries were oriented to the fiscal policies and used a combination of internal devaluation and tax policy measures. Despite their rather quick recovery, our second goal is to analyse the long term influence that the measures had on the national economy.

Keywords: Currency Board Arrangement, internal devaluation, exchange rate regime, Great recession.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2044

Authors: F. F. Howard, I. Yakubu, C. B. Boye, J. S. Y. Kuma

Abstract:

Natural and human activities, such as mining operations, expose the natural soil to adverse environmental conditions, leading to contamination of soil, groundwater, and surface water, which has negative effects on humans, flora, and fauna. Bare or partly exposed soil is most liable to fluvial erosion. This paper enumerates various methods used to identify, map, and model fluvial erosion in a mining environment. Classical, Artificial Intelligence (AI), and GIS methods have been reviewed. One of the many classical methods used to estimate river erosion is the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE model is easy to use. Its reliance on empirical relationships that may not always be applicable to specific circumstances or locations is a flaw. Other classical models for estimating fluvial erosion are the Soil and Water Assessment Tool (SWAT) and the Universal Soil Loss Equation (USLE). These models offer a more complete understanding of the underlying physical processes and encompass a wider range of situations. Although more difficult to utilise, they depend on the availability and dependability of input data for correctness. AI can help deal with multivariate and complex difficulties and predict soil loss with higher accuracy than traditional methods, and also be used to build unique models for identifying degraded areas. AI techniques have become popular as an alternative predictor for degraded environments. However, this research proposed a hybrid of classical, AI, and GIS methods for efficient and effective modelling of fluvial erosion.

Keywords: Fluvial erosion, classical methods, Artificial Intelligence, Geographic Information System.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 183

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

Abstract:

Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is widely used for LV segmentation, but it suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is improved to achieve a fast and efficient LV segmentation. First, a robust and efficient detection based on Hough forest localizes cardiac feature points. Such feature points are used to predict the initial fitting of the LV shape model. Second, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. With the robust initialization, ASM is able to achieve more accurate segmentation. The performance of the proposed method is evaluated on a dataset of 810 cardiac ultrasound images that are mostly abnormal shapes. This proposed method is compared with several combinations of ASM and existing initialization methods. Our experiment results demonstrate that accuracy of the proposed method for feature point detection for initialization was 40% higher than the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops and thus speeds up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: Hough forest, active shape model, segmentation, cardiac left ventricle.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1503

Authors: Chih Chin Yang, Yen Chun Lin, Hsiao Hsuan Cheng

Abstract:

Three similar negative differential resistance (NDR) profiles with both high peak to valley current density ratio (PVCDR) value and high peak current density (PCD) value in unity resonant tunneling electronic circuit (RTEC) element is developed in this paper. The PCD values and valley current density (VCD) values of the three NDR curves are all about 3.5 A and 0.8 A, respectively. All PV values of NDR curves are 0.40 V, 0.82 V, and 1.35 V, respectively. The VV values are 0.61 V, 1.07 V, and 1.69 V, respectively. All PVCDR values reach about 4.4 in three NDR curves. The PCD value of 3.5 A in triple PVCDR RTEC element is better than other resonant tunneling devices (RTD) elements. The high PVCDR value is concluded the lower VCD value about 0.8 A. The low VCD value is achieved by suitable selection of resistors in triple PVCDR RTEC element. The low PV value less than 1.35 V possesses low power dispersion in triple PVCDR RTEC element. The designed multiple value logical level (MVLL) system using triple PVCDR RTEC element provides equidistant logical level. The logical levels of MVLL system are about 0.2 V, 0.8 V, 1.5 V, and 2.2 V from low voltage to high voltage and then 2.2 V, 1.3 V, 0.8 V, and 0.2 V from high voltage back to low voltage in half cycle of sinusoid wave. The output level of four levels MVLL system is represented in 0.3 V, 1.1 V, 1.7 V, and 2.6 V, which satisfies the NMP condition of traditional two-bit system. The remarkable logical characteristic of improved MVLL system with paralleled capacitor are with four significant stable logical levels about 220 mV, 223 mV, 228 mV, and 230 mV. The stability and articulation of logical levels of improved MVLL system are outstanding. The average holding time of improved MVLL system is approximately 0.14 μs. The holding time of improved MVLL system is fourfold than of basic MVLL system. The function of additional capacitor in the improved MVLL system is successfully discovered.

Keywords: Capacitance, Logical level, Constant current source

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1389