Search results for: permittivity measurement techniques
6158 Developing a Machine Learning-based Cost Prediction Model for Construction Projects using Particle Swarm Optimization
Authors: Soheila Sadeghi
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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction
Procedia PDF Downloads 656157 A Multilevel Approach for Stroke Prediction Combining Risk Factors and Retinal Images
Authors: Jeena R. S., Sukesh Kumar A.
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Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.Keywords: prediction, retinal imaging, risk factors, stroke
Procedia PDF Downloads 3086156 Induction Machine Bearing Failure Detection Using Advanced Signal Processing Methods
Authors: Abdelghani Chahmi
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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation
Procedia PDF Downloads 1416155 Preventive Impact of Regional Analgesia on Chronic Neuropathic Pain After General Surgery
Authors: Beloulou Mohamed Lamine, Fedili Benamar, Meliani Walid, Chaid Dalila, Lamara Abdelhak
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Introduction: Post-surgical chronic pain (PSCP) is a pathological condition with a rather complex etiopathogenesis that extensively involves sensitization processes and neuronal damage. The neuropathic component of these pains is almost always present, with variable expression depending on the type of surgery. Objective: To assess the presumed beneficial effect of Regional Anesthesia-Analgesia Techniques (RAAT) on the development of post-surgical chronic neuropathic pain (PSCNP) in various surgical procedures. Patients and Methods: A comparative study involving 510 patients distributed across five surgical models (mastectomy, thoracotomy, hernioplasty, cholecystectomy, and major abdominal-pelvic surgery) and randomized into two groups: Group A (240) receiving conventional postoperative analgesia and Group B (270) receiving balanced analgesia, including the implementation of a Regional Anesthesia-Analgesia Technique (RAAT). These patients were longitudinally followed over a 6-month period, with postsurgical chronic neuropathic pain (PSCNP) defined by a Neuropathic Pain Score DN2≥ 3. Comparative measurements through univariate and multivariable analyses were performed to identify associations between the development of PSCNP and certain predictive factors, including the presumed preventive impact (protective effect) of RAAT. Results: At the 6th month post-surgery, 419 patients were analyzed (Group A= 196 and Group B= 223). The incidence of PSCNP was 32.2% (n=135). Among these patients with chronic pain, the prevalence of neuropathic pain was 37.8% (95% CI: [29.6; 46.5]), with n=51/135. It was significantly lower in Group B compared to Group A, with respective percentages of 31.4% vs. 48.8% (p-value = 0.035). The most significant differences were observed in breast and thoracopulmonary surgeries. In a multiple regression analysis, two predictors of PSCNP were identified: the presence of preoperative pain at the surgical site as a risk factor (OR: 3.198; 95% CI [1.326; 7.714]) and RAAT as a protective factor (OR: 0.408; 95% CI [0.173; 0.961]). Conclusion: The neuropathic component of PSCNP can be observed in different types of surgeries. Regional analgesia included in a multimodal approach to postoperative pain management has proven to be effective for acute pain and seems to have a preventive impact on the development of PSCNP and its neuropathic nature, particularly in surgeries that are more prone to chronicization.Keywords: post-surgical chronic pain, post-surgical chronic neuropathic pain, regional anesthesia-analgesia techniques, neuropathic pain score DN2, preventive impact
Procedia PDF Downloads 816154 Effect of Polarized Light Therapy on Oral Mucositis in Cancer Patients Receiving Chemotherapy
Authors: Zakaria Mowafy Emam Mowafy, Hamed Abd Allah Hamed, Marwa Mahmoud Abd-Elmotalb, Andrew Anis Fakhray Mosaad
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The purpose of this paper is to determine the efficacy of polarized light therapy for chemotherapy-treated cancer patients who have oral mucositis. Methods of evaluation are the measurement of the WHO oral mucositis scale and the common toxicity criteria scale. Methods: Thirty cancer patients receiving chemotherapy (males and females) who had oral mucositis and ulceration pain, and their ages ranged from 30 to 55 years, were divided into two groups. Group (A), composed of 15 patients, received the Bioptron light therapy (BLT) in addition to the routine medical care of oral mucositis. Group (B) received only the routine medical care of oral mucositis; the duration of the BLT application was 10 minutes applied daily for 30 days. Results and conclusion: Results showed that the application of the BLT had valuable healing effects on oral mucositis in cancer patients receiving chemotherapy, as evidenced by the high decreases of the WHO oral mucositis scale and the common toxicity criteria scale.Keywords: Bioptron light therapy, oral mucositis, WHO oral mucositis scale, common toxicity criteria scale
Procedia PDF Downloads 1146153 The Green Synthesis AgNPs from Basil Leaf Extract
Authors: Wanida Wonsawat
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Bioreduction of silver nanoparticles (AgNPs) from silver ions (Ag+) using water extract of Thai basil leaf was successfully carried out. The basil leaf extract provided a reducing agent and stabilizing agent for a synthesis of metal nanoparticles. Silver nanoparticles received from cut and uncut basil leaf was compared. The resulting silver nanoparticles are characterized by UV-Vis spectroscopy. The maximum intensities of silver nanoparticle from cut and uncut basil leaf were 410 and 420, respectively. The techniques involved are simple, eco-friendly and rapid.Keywords: basil leaves, silver nanoparticles, green synthesis, plant extract
Procedia PDF Downloads 5966152 Prediction of Concrete Hydration Behavior and Cracking Tendency Based on Electrical Resistivity Measurement, Cracking Test and ANSYS Simulation
Authors: Samaila Muazu Bawa
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Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were separately monitored using non-contact electrical resistivity apparatus, a plastic ring mould and penetration resistance method respectively. The results show highest resistivity of C30 at the beginning until reaching the acceleration point when C50 accelerated and overtaken the others, and this period corresponds to its final setting time range, from resistivity derivative curve, hydration process can be divided into dissolution, induction, acceleration and deceleration periods, restrained shrinkage crack and setting time tests demonstrated the earliest cracking and setting time of C50, therefore, this method conveniently and rapidly determines the concrete’s crack potential. The highest inflection time (ti), the final setting time (tf) were obtained and used with crack time in coming up with mathematical models for the prediction of concrete’s cracking age for the range being considered. Finally, ANSYS numerical simulations supports the experimental findings in terms of the earliest crack age of C50 and the crack location that, highest stress concentration is always beneath the artificially introduced expansion joint of C50.Keywords: concrete hydration, electrical resistivity, restrained shrinkage crack, ANSYS simulation
Procedia PDF Downloads 2426151 The Effect of Supplementary Cementitious Materials on Fresh and Hardened Properties of Self-Compacting Concretes
Authors: Akram Salah Eddine Belaidi, Said Kenai, El-Hadj Kadri, Benchaâ Benabed, Hamza Soualhi
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Self-compacting concrete (SCC) was developed in the middle of the 1980’s in Japan. SCC flows alone under its dead weight and consolidates itself without any entry of additional compaction energy and without segregation. As an integral part of a SCC, self-compacting mortars (SCM) may serve as a basis for the mix design of concrete since the measurement of the rheological properties of SCCs. This paper discusses the effect of using natural pozzolana (PZ) and marble powder (MP) in two alternative systems ratios PZ/MP = 1 and 1/3 of the performance of the SCC. A total of 11 SCC’s were prepared having a constant water-binder (w/b) ratio of 0.40 and total cementitious materials content of 475 kg/m3. Then, the fresh properties of the mortars were tested for mini-slump flow diameter and mini-V-funnel flow time for SCMs and Slumps flow test, L-Box height ratio, V-Funnel flow time and sieve stability for SCC. Moreover, the development in the compressive strength was determined at 3, 7, 28, 56, and 90 days. Test results have shown that using of ternary blends improved the fresh properties of the mixtures. The compressive strength of SCC at 90 days with 30% of PZ and MP was similar to those of ordinary concrete use in situ.Keywords: self-compacting mortar, self-compacting concrete, natural pozzolana, marble powder, rheology, compressive strength
Procedia PDF Downloads 3786150 Optimization of Robot Motion Planning Using Biogeography Based Optimization (Bbo)
Authors: Jaber Nikpouri, Arsalan Amralizadeh
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In robotics manipulators, the trajectory should be optimum, thus the torque of the robot can be minimized in order to save power. This paper includes an optimal path planning scheme for a robotic manipulator. Recently, techniques based on metaheuristics of natural computing, mainly evolutionary algorithms (EA), have been successfully applied to a large number of robotic applications. In this paper, the improved BBO algorithm is used to minimize the objective function in the presence of different obstacles. The simulation represents that the proposed optimal path planning method has satisfactory performance.Keywords: biogeography-based optimization, path planning, obstacle detection, robotic manipulator
Procedia PDF Downloads 3086149 Application of Medium High Hydrostatic Pressure in Preserving Textural Quality and Safety of Pineapple Compote
Authors: Nazim Uddin, Yohiko Nakaura, Kazutaka Yamamoto
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Compote (fruit in syrup) of pineapple (Ananas comosus L. Merrill) is expected to have a high market potential as one of convenient ready-to-eat (RTE) foods worldwide. High hydrostatic pressure (HHP) in combination with low temperature (LT) was applied to the processing of pineapple compote as well as medium HHP (MHHP) in combination with medium-high temperature (MHT) since both processes can enhance liquid impregnation and inactivate microbes. MHHP+MHT (55 or 65 °C) process, as well as the HHP+LT process, has successfully inactivated the microbes in the compote to a non-detectable level. Although the compotes processed by MHHP+MHT or HHP+LT have lost the fresh texture as in a similar manner as those processed solely by heat, it was indicated that the texture degradations by heat were suppressed under MHHP. Degassing process reduced the hardness, while calcium (Ca) contributed to be retained hardness in MHT and MHHP+MHT processes. Electrical impedance measurement supported the damage due to degassing and heat. The color, Brix, and appearance were not affected by the processing methods significantly. MHHP+MHT and HHP+LT processes may be applicable to produce high-quality, safe RTE pineapple compotes. Further studies on the optimization of packaging and storage condition will be indispensable for commercialization.Keywords: compote of pineapple, RTE, medium high hydrostatic pressure, postharvest loss, texture
Procedia PDF Downloads 1416148 Development of a Data-Driven Method for Diagnosing the State of Health of Battery Cells, Based on the Use of an Electrochemical Aging Model, with a View to Their Use in Second Life
Authors: Desplanches Maxime
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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression
Procedia PDF Downloads 746147 Voltage Stability Assessment and Enhancement Using STATCOM -A Case Study
Authors: Puneet Chawla, Balwinder Singh
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Recently, increased attention has been devoted to the voltage instability phenomenon in power systems. Many techniques have been proposed in the literature for evaluating and predicting voltage stability using steady state analysis methods. In this paper, P-V and Q-V curves have been generated for a 57 bus Patiala Rajpura circle of India. The power-flow program is developed in MATLAB using Newton-Raphson method. Using Q-V curves, the weakest bus of the power system and the maximum reactive power change permissible on that bus is calculated. STATCOMs are placed on the weakest bus to improve the voltage and hence voltage stability and also the power transmission capability of the line.Keywords: voltage stability, reactive power, power flow, weakest bus, STATCOM
Procedia PDF Downloads 5196146 Effect of Traffic Volume and Its Composition on Vehicular Speed under Mixed Traffic Conditions: A Kriging Based Approach
Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh
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Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.Keywords: speed, Kriging, arterial, traffic volume
Procedia PDF Downloads 3576145 Model Predictive Controller for Pasteurization Process
Authors: Tesfaye Alamirew Dessie
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Our study focuses on developing a Model Predictive Controller (MPC) and evaluating it against a traditional PID for a pasteurization process. Utilizing system identification from the experimental data, the dynamics of the pasteurization process were calculated. Using best fit with data validation, residual, and stability analysis, the quality of several model architectures was evaluated. The validation data fit the auto-regressive with exogenous input (ARX322) model of the pasteurization process by roughly 80.37 percent. The ARX322 model structure was used to create MPC and PID control techniques. After comparing controller performance based on settling time, overshoot percentage, and stability analysis, it was found that MPC controllers outperform PID for those parameters.Keywords: MPC, PID, ARX, pasteurization
Procedia PDF Downloads 1676144 Analysis of Histogram Asymmetry for Waste Recognition
Authors: Janusz Bobulski, Kamila Pasternak
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Despite many years of effort and research, the problem of waste management is still current. So far, no fully effective waste management system has been developed. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.Keywords: waste management, environmental protection, image processing, computer vision
Procedia PDF Downloads 1246143 Nanowire by Ac Electrodeposition Into Nanoporous Alumina Fabrication of High Aspect Ratio Metalic
Authors: M. Beyzaiea, S. Mohammadia
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High aspect ratio metallic (silver, cobalt) nanowire arrays were fabricated using ac electrodeposition techniques into the nanoporous alumina template. The template with long pore dept fabricated by hard anodization (HA) and thinned for ac electrodeposition. Template preparation was done in short time by using HA technique and high speed thing process. The TEM and XRD investigation confirm the three dimensional nucleation growth mechanism of metallic nanowire inside the nanoporous alumina that fabricated by HA process.Keywords: metallic, nanowire, nanoporous alumina, ac electrodeposition
Procedia PDF Downloads 2776142 Perceptions and Attitudes toward Pain in Patients with Chronic Low-Back Pain
Authors: Naomi Sato, Tomonori Sato, Kenji Masui, Rob Stanborough
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To date, there are few studies on the subjective experiences of patients with chronic low-back pain (CLBP). The purpose of this study was to gain a better understanding of CLBP patients’ perceptions and attitudes regarding pain. Individual, semi-constructed interviews were conducted with 7 Japanese and 10 Americans who had been diagnosed with CLBP. The interviews were transcribed verbatim and analyzed based on a content analysis approach. The study proposal was approved by the Institutional Review Board of the first author’s affiliate university. All participants provided written consent. Participants’ ages ranged from 48 to 82. Five main categories were emerged, namely, 'There are no reasons for long-term chronic pain,' 'Just will not worsen,' 'Have something to help me cope,' 'Pain restricts my life,' and 'Have something to relieve me.' Participants lived with CLBP, which could sometimes be avoided as a result of the coping strategies that they employed, and due to which they sometimes felt helpless, despite their efforts. As a result, they had mixed feelings, which included resignation, resoluteness, and optimism. However, their perceptions and attitudes toward pain seemed to differ based on their backgrounds, including biological, social, religious, and cultural status. There is a need for the development of a scale in future studies, to enable quantitative measurement of individuals’ perceptions of and attitudes toward pain. There is also a need for an investigation of factors influencing perceptions and attitudes toward pain.Keywords: attitude, chronic low-back pain, perception, qualitative study
Procedia PDF Downloads 2576141 Difference between 'HDR Ir-192 and Co-60 Sources' for High Dose Rate Brachytherapy Machine
Authors: Md Serajul Islam
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High Dose Rate (HDR) Brachytherapy is used for cancer patients. In our country’s prospect, we are using only cervices and breast cancer treatment by using HDR. The air kerma rate in air at a reference distance of less than a meter from the source is the recommended quantity for the specification of gamma ray source Ir-192 in brachytherapy. The absorbed dose for the patients is directly proportional to the air kerma rate. Therefore the air kerma rate should be determined before the first use of the source on patients by qualified medical physicist who is independent from the source manufacturer. The air kerma rate will then be applied in the calculation of the dose delivered to patients in their planning systems. In practice, high dose rate (HDR) Ir-192 afterloader machines are mostly used in brachytherapy treatment. Currently, HDR-Co-60 increasingly comes into operation too. The essential advantage of the use of Co-60 sources is its longer half-life compared to Ir-192. The use of HDRCo-60 afterloading machines is also quite interesting for developing countries. This work describes the dosimetry at HDR afterloading machines according to the protocols IAEA-TECDOC-1274 (2002) with the nuclides Ir-192 and Co-60. We have used 3 different measurement methods (with a ring chamber, with a solid phantom and in free air and with a well chamber) in dependence of each of the protocols. We have shown that the standard deviations of the measured air kerma rate for the Co-60 source are generally larger than those of the Ir-192 source. The measurements with the well chamber had the lowest deviation from the certificate value. In all protocols and methods, the deviations stood for both nuclides by a maximum of about 1% for Ir-192 and 2.5% for Co-60-Sources respectively.Keywords: Ir-192 source, cancer, patients, cheap treatment cost
Procedia PDF Downloads 2436140 Application of Low-order Modeling Techniques and Neural-Network Based Models for System Identification
Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo
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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.Keywords: the bluff body wakes, low-order modeling, neural network, system identification
Procedia PDF Downloads 1886139 Cyclostationary Analysis of Polytime Coded Signals for LPI Radars
Authors: Metuku Shyamsunder, Kakarla Subbarao, P. Prasanna
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In radars, an electromagnetic waveform is sent, and an echo of the same signal is received by the receiver. From this received signal, by extracting various parameters such as round trip delay, Doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper, a brief discussion on LPI radar and its modulation (polytime code (PT1)), detection (cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity.Keywords: LPI radar, polytime codes, cyclostationary DFSM, FAM
Procedia PDF Downloads 4796138 A Bayesian Multivariate Microeconometric Model for Estimation of Price Elasticity of Demand
Authors: Jefferson Hernandez, Juan Padilla
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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.Keywords: price elasticity, volume, correlation structures, Bayesian models
Procedia PDF Downloads 1716137 Development of a Shape Based Estimation Technology Using Terrestrial Laser Scanning
Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park
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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement
Procedia PDF Downloads 2416136 Evaluation of the Impact of Functional Communication Training on Behaviors of Concern for Students at a Non-Maintained Special School
Authors: Kate Duggan
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Introduction: Functional Communication Training (FCT) is an approach which aims to reduce behaviours of concern by teaching more effective ways to communicate. It requires identification of the function of the behaviour of concern, through gathering information from key stakeholders and completing observations of the individual’s behaviour including antecedents to, and consequences of the behaviour. Appropriate communicative alternatives are then identified and taught to the individual using systematic instruction techniques. Behaviours of concern demonstrated by individuals with autism spectrum conditions (ASC) frequently have a communication function. When contributing to positive behavior support plans, speech and language therapists and other professionals working with individuals with ASC need to identify alternative communicative behaviours which are equally reinforcing as the existing behaviours of concern. Successful implementation of FCT is dependent on an effective ‘response match’. The new way of communicating must be equally as effective as the behaviour previously used and require the same amount or less effort from the individual. It must also be understood by the communication partners the individual encounters and be appropriate to their communicative contexts. Method: Four case studies within a non-maintained special school environment were described and analysed. A response match framework was used to identify the effectiveness of functional communication training delivered by the student’s speech and language therapist, teacher and learning support assistants. The success of systematic instruction techniques used to develop new communicative behaviours was evaluated using the CODES framework. Findings: Functional communication training can be used as part of a positive behaviour support approach for students within this setting. All case studies reviewed demonstrated ‘response success’, in that the desired response was gained from the new communicative behaviour. Barriers to the successful embedding of new communicative behaviours were encountered. In some instances, the new communicative behaviour could not be consistently understood across all communication partners which reduced ‘response recognisability’. There was also evidence of increased physical or cognitive difficulty in employing the new communicative behaviour which reduced the ‘response effectivity’. Successful use of ‘thinning schedules of reinforcement’, taught students to tolerate a delay to reinforcement once the new communication behaviour was learned.Keywords: augmentative and alternative communication, autism spectrum conditions, behaviours of concern, functional communication training
Procedia PDF Downloads 1206135 Increasing the Competitiveness of Batik Products as a Ready-To-Wear Cash Material Through Patterned Batik Innovation with Quilting Technique, at Klampar Batik Tourism Village
Authors: Urip Wahyuningsih, Indarti, Yuhri Inang Prihatina
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The current development of batik art has given rise to various batik industries. The emergence of the batik industry is in order to meet the needs of the increasing share of the batik fashion market. This gives rise to competitiveness between the batik industry to compete for a share of the existing batik clothing market. Conditions like this also occur in Klampar Pamekasan Maduira Village, as one of the Batik Tourism Villages in Indonesia, it must continue to improve by trying to maintain the characteristics of Klampar Pamekasan Madura batik fashion and must also always innovate so that it remains highly competitive so that it remains one of the places popular batik tourist destination. Ready-to-wear or ready-to-wear clothing is clothing that is mass produced and produced in various sizes and colors, which can be purchased directly and worn easily. Patterned batik cloth is basically batik cloth that has the pattern lines of the clothing parts arranged efficiently, so there is no need to bother designing the pattern layout of the clothing parts on the batik cloth to be cut. Quilting can be defined as the art of combining fabric materials of certain sizes and cuts to form unique motifs. Based on several things above, breakthrough production innovation is needed without abandoning the characteristic of Klampar Pamekasan Madura Batik as one of the Batik Tourism Villages in Indonesia. One innovation that can be done is creating ready-to-wear patterned batik clothing products using a quilting technique. The method used in this research is the Double Diamond Design Process method. This method is divided into 4 phases namely, discover (namely the stage of designing the theme of the ready-to-wear patterned batik fashion innovation concept using quilting techniques in the Batik Village, Klampar Village, Pamekasasan, Madura), define (determine the design summary and present challenges to the design), develop ( presents prototypes developed, tested, reviewed and refined) and deliver (selected designs are produced, pass final tests and are ready to be commercialized). The research produces patterned batik products that are ready to wear with quilting techniques that are validated by experts and accepted by the public.Keywords: competitiveness, ready to wear, innovation, quilting, klampar batik vllage
Procedia PDF Downloads 536134 Synthesis and Characterisation of Bi-Substituted Magnetite Nanoparticles by Mechanochemical Processing (MCP)
Authors: Morteza Mohri Esfahani, Amir S. H. Rozatian, Morteza Mozaffari
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Single phase magnetite nanoparticles and Bi-substituted ones were prepared by mechanochemical processing (MCP). The effects of Bi-substitution on the structural and magnetic properties of the nanoparticles were studied by X-ray Diffraction (XRD) and magnetometry techniques, respectively. The XRD results showed that all samples have spinel phase and by increasing Bi content, the main diffraction peaks were shifted to higher angles, which means the lattice parameter decreases from 0.843 to 0.838 nm and then increases to 0.841 nm. Also, the results revealed that increasing Bi content lead to a decrease in saturation magnetization (Ms) from 74.9 to 48.8 emu/g and an increase in coercivity (Hc) from 96.8 to 137.1 Oe.Keywords: bi-substituted magnetite nanoparticles, mechanochemical processing, X-ray diffraction, magnetism
Procedia PDF Downloads 5396133 Effect of Chemical Concentration on the Rheology of Inks for Inkjet Printing
Authors: M. G. Tadesse, J. Yu, Y. Chen, L. Wang, V. Nierstrasz, C. Loghin
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Viscosity and surface tension are the fundamental rheological property of an ink for inkjet printing. In this work, we optimized the viscosity and surface tension of inkjet inks by varying the concentration of glycerol with water, PEDOT:PSS with glycerol and water, finally by adding the surfactant. The surface resistance of the sample was characterized by four-probe measurement principle. The change in volume of PEDOT:PSS in water, as well as the change in weight of glycerol in water has got a great influence on the viscosity on both temperature dependence and shear dependence behavior of the ink solution. The surface tension of the solution changed from 37 to 28 mN/m due to the addition of Triton. Varying the volume of PEDOT:PSS and the volume of glycerol in water has a great influence on the viscosity of the ink solution for inkjet printing. Viscosity drops from 12.5 to 9.5 mPa s with the addition of Triton at 25 oC. The PEDOT:PSS solution was found to be temperature dependence but not shear dependence as it is a Newtonian fluid. The sample was used to connect the light emitting diode (LED), and hence the electrical conductivity, with a surface resistance of 0.158 KΩ/square, was sufficient enough to give transfer current for LED lamp. The rheology of the inkjet ink is very critical for the successful droplet formation of the inkjet printing.Keywords: shear rate, surface tension, surfactant, viscosity
Procedia PDF Downloads 1746132 Fuel Quality of Biodiesel from Chlorella protothecoides Microalgae Species
Authors: Mukesh Kumar, Mahendra Pal Sharma
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Depleting fossil fuel resources coupled with serious environmental degradation has led to the search for alternative resources for biodiesel production as a substitute of Petro-diesel. Currently, edible, non-edible oils and microalgal plant species are cultivated for biodiesel production. Looking at the demerits of edible and non-edible oil resources, the focus is being given to grow microalgal species having high oil productivities, less maturity time and less land requirement. Out of various microalgal species, Chlorella protothecoides is considered as the most promising species for biodiesel production owing to high oil content (58 %), faster growth rate (24–48 h) and high biomass productivity (1214 mg/l/day). The present paper reports the results of optimization of reaction parameters of transesterification process as well as the kinetics of transesterification with 97% yield of biodiesel. The measurement of fuel quality of microalgal biodiesel shows that the biodiesel exhibit very good oxidation stability (O.S) of 7 hrs, more than ASTM D6751 (3 hrs) and EN 14112 (6 hrs) specifications. The CP and PP of 0 and -3 °C are finding as per ASTM D 2500-11 and ASTM D 97-12 standards. These results show that the microalgal biodiesel does not need any enhancement in O.S & CFP and hence can be recommended to be directly used as MB100 or its blends into diesel engine operation. Further, scope is available for the production of binary blends using poor quality biodiesel for engine operation.Keywords: fuel quality, methyl ester yield, microalgae, transesterification
Procedia PDF Downloads 2196131 Life Prediction of Cutting Tool by the Workpiece Cutting Condition
Authors: Noemia Gomes de Mattos de Mesquita, José Eduardo Ferreira de Oliveira, Arimatea Quaresma Ferraz
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Stops to exchange cutting tool, to set up again the tool in a turning operation with CNC or to measure the workpiece dimensions have a direct influence on production. The premature removal of the cutting tool results in high cost of machining since the parcel relating to the cost of the cutting tool increases. On the other hand, the late exchange of cutting tool also increases the cost of production because getting parts out of the preset tolerances may require rework for its use when it does not cause bigger problems such as breaking of cutting tools or the loss of the part. Therefore, the right time to exchange the tool should be well defined when wanted to minimize production costs. When the flank wear is the limiting tool life, the time predetermination that a cutting tool must be used for the machining occurs within the limits of tolerance can be done without difficulty. This paper aims to show how the life of the cutting tool can be calculated taking into account the cutting parameters (cutting speed, feed and depth of cut), workpiece material, power of the machine, the dimensional tolerance of the part, the finishing surface, the geometry of the cutting tool and operating conditions of the machine tool, once known the parameters of Taylor algebraic structure. These parameters were raised for the ABNT 1038 steel machined with cutting tools of hard metal.Keywords: machining, productions, cutting condition, design, manufacturing, measurement
Procedia PDF Downloads 6396130 A Comparative Analysis about the Effects of a Courtyard in Indoor Thermal Environment of a Room with and without Transitional Space Adjacent to Courtyard of a House in Old Dhaka, Bangladesh
Authors: Fatema Tasmia, Brishti Majumder, Atiqur Rahman
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Attaining appropriate comfort conditions in a place where the climate is hot and humid can be perplexing. Especially, when it is resided at a congested place like old Dhaka Bangladesh, the provision of giving cross ventilation and building with proper orientation is quite difficult. Courtyards are the part of buildings which are used as space for outdoor household activities, social gathering and it is also proved to have indoor thermal comfort as an effect of courtyard. This paper aims to investigate the effect of courtyard in indoor thermal environment of a room adjacent to the courtyard and a room next to transitional space after a courtyard through field measurements of a case study house. The field measurement was conducted in a two-storey house. Among different aspects of thermal environment, the study of this paper is based on the analysis of temperature in both situations. Ventilation or air movement was considered to have no impact because of the rooms’ layout and location. Other aspects and their variables were considered as constant (especially material) for accuracy and avoidance of confusion. This study focuses on the outcome that can ultimately contribute to the configuration of courtyards and in its relation to indoor space while achieving thermal comfort.Keywords: courtyard, old Dhaka, temperature, thermal comfort, transitional space
Procedia PDF Downloads 2286129 Study of Poly(Ethylene Terephthalate)-Clay Nanocomposites Prepareted by Extrusion Reactive Method
Authors: F. Zouai, F. Z. Benabid, S. Bouhelal, D. Benachour
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A method for the exfoliation of polyethylene terephtalate (PET) - clay nanocomposites has been reported in this study. Montmorillonite clay based polyethylene terephtalate nanocomposites were prepared by reactive melt-mixing. To achieve this, untreated clay was first functionalized with the crosslinking agent compound based mainly on peroxide/sulphur and TMTD as accelerator or activator for sulphur. Furthermore, the different blends composition of PET/clay were directly mixed in melt state in closed chamber of plastograph at given working conditions for short time and in one step process. To investigate the microstructure modification and thermal, mechanical and rheological properties the DSC, WAXS, microhardness, FTIR and tensile properties were performed. The resulting structure of the modified samples shows that total exfoliation appears at 4% w/w of clay to PET matrices. The crystallinity and tensile modulus were correlated by the H microhardness and the DSC shows no significant effect on the cristallinity degree. The mechanical properties were improved significantly. The viscosity decreases for 4% clay and the activation energy is the minimum. The WAXS measurement shows a partial exfoliation without any intercalation which is the most relevant point. The grafting of organic to inorganic nanolayers was observed by Si—O—C and Si—C bonds by FTIR.Keywords: PET, montmorillonite, nanocomposites, exfoliation, reactive melt-mixing
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