Search results for: slice thickness accuracy

Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

Procedia PDF Downloads 160

Authors: Beghdadi Lotfi

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In the present work a numerical method is proposed in order to optimize the thermal performance of finned surfaces. The bidimensional temperature distribution on the longitudinal section of the fin is calculated by restoring to the finite volumes method. The heat flux dissipated by a generic profile fin is compared with the heat flux removed by the rectangular profile fin with the same length and volume. In this study, it is shown that a finite volume method for quadrilaterals unstructured mesh is developed to predict the two dimensional steady-state solutions of conduction equation, in order to determine the sinusoidal parameter values which optimize the fin effectiveness. In this scheme, based on the integration around the polygonal control volume, the derivatives of conduction equation must be converted into closed line integrals using same formulation of the Stokes theorem. The numerical results show good agreement with analytical results. To demonstrate the accuracy of the method, the absolute and root-mean square errors versus the grid size are examined quantitatively.

Keywords: Stokes theorem, unstructured grid, heat transfer, complex geometry, effectiveness

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Authors: Mikhail Gritskevich, Sebastian Hohenstein

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The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.

Keywords: discrete holes film cooling, Reynolds Averaged Navier-Stokes (RANS), Reynolds stress tensor anisotropy, turbulent heat transfer

Procedia PDF Downloads 422

Authors: Amir Raeisdana, Davood Sohrabi, Mojtaba Nohekhan, Ameneh Kargarian, Maryam Ghapanvari, Alireza Aslezaeem

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Improvement of zirconium properties by chromium coating and nitrogen implantation is ideal to protect the nuclear fuel rods against corrosion and secondary hydrogenation. Metallic chromium (Cr) has attracted attention as a potential coating material on zirconium alloys, to limit external cladding corrosion. In this research, high energy plasma focus device was used to coat the chromium and implant the nitrogen ions in the zirconium substrate. This device emits high-energy nitrogen ions of 10 keV-1 MeV and with a flux of 10^16 ions/cm^2 in each shot toward the target so it is attractive for implantation on the substrate materials at the room temperature. Six zirconium samples in 2cm×2cm dimensions with 1mm thickness were located at a distance of 20cm from the place where the pinch is formed. The experiments are carried out in 0.5 mbar of the nitrogen gas pressure and 15 kV of the charging voltage. Pure Cr disc was installed on the anode head for sputtering of the chromium and deposition on zirconium substrate. When the pinch plasma column decays due to various instabilities, intense and high-energy N2 ions are accelerated towards the zirconium substrate also sputtered Cr is deposited on the zirconium substrate. XRD and XRF analysis were used to study the structural properties of the samples. XRF analysis indicates 77.1% of Zr and 11.1% of Cr in the surface of the sample. XRD spectra shows the formation of ZrN, CrN and CrZr composites after nitrogen implantation and chromium coating. XRD spectra shows the chromium peak height equal to 152.80 a.u. for the major sample (θ=0֯) and 92.99 a.u. for the minor sample (θ=6֯), so implantation and coating along the main axis of the device is significantly more than other directions.

Keywords: ZrN and CrN and CrZr composites, angular distribution for Cr deposition rate, zirconium corrosion resistance, nuclear fuel rods, plasma focus device

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Authors: R. Ziaie Moayed, H. Keshavarz Hedayati

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Over recent years, due to increased population and increased waste production, groundwater protection has become more important, therefore, designing engineered barrier systems such as landfill liners to prevent the entry of leachate into groundwater should be done with greater accuracy. These measures generally involve the application of low permeability soils such as clays. Bentonite is a natural clay with low permeability which makes it a suitable soil for using in liners. Also zeolite with high cation exchange capacity can help to reduce of hazardous materials risk. Bentonite expands when wet, absorbing as much as several times its dry mass in water. This property may effect on some structural properties of soil such as shear strength. In present study, shear strength parameters are determined by both leachates polluted and not polluted bentonite-amended zeolite soil with mixing rates (B/Z) of 5%-10% and 20% with unconfined compression test to obtain the differences. It is shown that leachate presence causes reduction in resistance in general.

Keywords: bentonite, leachate, shear strength parameters, unconfined compression test

Procedia PDF Downloads 110

Authors: Chattrarat Hotrawaisaya

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This research aims to formulate the logistics collaborative model which is the management tool for orchid flower exporter. The researchers study logistics activities in orchid supply chain that stakeholders can collaborate and develop, including demand forecasting, inventory management, warehouse and storage, order-processing, and transportation management. The research also explores logistics collaboration implementation into orchid’s stakeholders. The researcher collected data before implementation and after model implementation. Consequently, the costs and efficiency were calculated and compared between pre and post period of implementation. The research found that the results of applying the logistics collaborative model to orchid exporter reduces inventory cost and transport cost. The model also improves forecasting accuracy, and synchronizes supply chain of exporter. This research paper contributes the uniqueness logistics collaborative model which value to orchid industry in Thailand. The orchid exporters may use this model as their management tool which aims in competitive advantage.

Keywords: logistics, orchid, supply chain, collaboration

Procedia PDF Downloads 441

Authors: Mohammed Masum, Mohammad Omer Faruk Khan, Md. Nazwanul Haque, Anwar Sadat Md. Sayem, Md. Azhar Hossain

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The study area is the Hakaluki Haor which is the second largest wet land of Bangladesh. It spans over the districts of Moulvibazar and Sylhet in southeast Bangladesh. The study was focused in the exploration of peat reserve, reconstruction of the paleo-environment as well as the utilization of the peat resources. Peat is found randomly from 0.5 m to 7 m below the surface and 1 m to 11 m thickness at over 40 beels as well as small plain lands of 90 km2 area of Hakaluki Haor. The total reserve of peat is 282 million ton in wet condition and 112 million ton in dry condition. The peat deposits of Hakaluki Haor area is the largest peat reserves of the Bangladesh. Peat bearing Hakaluki Haor is a low-lying wet land which geological term is synclinal depression. It may be a syncline between two anticlines which was filled with sediments as well as various plant materials derived from the hilly region (anticline) on both sides (west and east) of the Haor. The transportation may be triggered by large natural disasters or any tectonic reason. On the other hand vegetation occurred in this depression as aquatic plants which might have been destroyed by large natural disasters or any tectonic reason. As environment dictates the characteristics and the source of sediments, various aspects of the sediment are indicators of the environment. Peat has mainly industrial importance as a fuel for power production, traditionally used for cooking, domestic heating and in brick fields, also used as insulator in many industries, agricultural purposes, retaining moisture in soil, raw material in horticulture and colour industries etc. Power plants of about 100 MW capacities may be established in this region based on peat of Hakaluki Haor which may be continued more than one hundred years.

Keywords: peat, pale environment, Hakaluki Haor, beel, syncline, anticline

Procedia PDF Downloads 427

Authors: Afshin Zohdi, Selçuk Özdemir, Mustafa Aksoy

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Tungsten carbide-cobalt (WC-Co) is a widely utilized material for cold forming dies, including those employed in fastener production. In this study, we investigated the effectiveness of the pack boriding method in improving the surface properties of WC-Co cold forging dies. The boriding process involved embedding WC-Co samples, along with a steel control sample, within a chamber made of H13 tool steel. A boriding powder mixture was introduced into the chamber, which was then sealed using a paste. Subsequently, the samples were subjected to a temperature of 700°C for 5 hours in a furnace. Microstructural analysis, including cross-sectional examination and scanning electron microscopy (SEM), confirmed successful boron diffusion and its presence on the surface of the borided samples. The microhardness of the borided layer was significantly increased (3980 HV1) compared to the unborided sample (1320 HV3), indicating enhanced hardness. The borided layer exhibited an acceptable thickness of 45 microns, with a diffusion coefficient of 1.125 × 10-7 mm²/s, signifying a moderate diffusion rate. Energy-dispersive X-ray spectroscopy (EDS) mapping revealed an increase in boron content, desirable for the intended purpose, while an undesired increase in oxygen content was observed. Furthermore, the pin-on-disk wear test demonstrated a reduction in friction coefficient, indicating improved mechanical and tribological properties of the surface. The successful implementation of the pack boriding process highlights its potential for enhancing the performance of WC-Co cold forging dies.

Keywords: WC-Co, cold forging dies, pack boriding, surface hardness, wear resistance, microhardness, diffusion coefficient, scanning electron microscopy, energy-dispersive X-ray spectroscopy

Procedia PDF Downloads 83

Authors: Nimisha Elsa Koshy, Varun P. Gopi, V. I. Thajudin Ahamed

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The entire visualization of GastroIntestinal (GI) tract is not possible with conventional endoscopic exams. Wireless Capsule Endoscopy (WCE) is a low risk, painless, noninvasive procedure for diagnosing diseases such as bleeding, polyps, ulcers, and Crohns disease within the human digestive tract, especially the small intestine that was unreachable using the traditional endoscopic methods. However, analysis of massive images of WCE detection is tedious and time consuming to physicians. Hence, researchers have developed software methods to detect these diseases automatically. Thus, the effectiveness of WCE can be improved. In this paper, a novel textural feature extraction method is proposed based on Contourlet transform and Log Gabor filter to distinguish ulcer regions from normal regions. The results show that the proposed method performs well with a high accuracy rate of 94.16% using Support Vector Machine (SVM) classifier in HSV colour space.

Keywords: contourlet transform, log gabor filter, ulcer, wireless capsule endoscopy

Procedia PDF Downloads 541

Authors: Amina Lyria Deghal Cheridi, Abla Chaker, Ahcene Loubar

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Relap5 system code is one among powerful tools, which is used in the area of design and safety evaluation. This work aims to simulate the behavior of a radiant steam boiler at the steady-state conditions using Relap5 code system. To perform this study, a detailed Relap5 model is built including all the parts of the steam boiler. The control and regulation systems are also considered. To reproduce the most important parameters and phenomena with an acceptable accuracy and fidelity, a strong qualification work is undertaken concerning the facility nodalization. It consists of making a comparison between the code results and the plant available data in steady-state operation mode. Therefore, the model qualification results at the steady-state are in good agreement with the steam boiler experimental data. The steam boiler Relap5 model has proved satisfactory; and the model was capable of predicting the main thermal-hydraulic steady-state conditions of the steam boiler.

Keywords: industrial steam boiler, model qualification, natural circulation, relap5/mod3.2, steady state simulation

Procedia PDF Downloads 274

Authors: G. Traini, G. Battistoni, F. Collamati, E. De Lucia, R. Faccini, C. Mancini-Terracciano, M. Marafini, I. Mattei, S. Muraro, A. Sarti, A. Sciubba, E. Solfaroli Camillocci, M. Toppi, S. M. Valle, C. Voena, V. Patera

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In Particle Therapy (PT) treatments a large amount of secondary particles, whose emission point is correlated to the dose released in the crossed tissues, is produced. The measurement of the secondary charged fragments component could represent a valid technique to monitor the beam range during the PT treatments, that is a still missing item in the clinical practice. A sub-millimetrical precision on the beam range measurement is required to significantly optimise the technique and to improve the treatment quality. In this contribution, a detector, named Dose Profiler (DP), is presented. It is specifically planned to monitor on-line the beam range exploiting the secondary charged particles produced in PT Carbon ions treatment. In particular, the DP is designed to track the secondary fragments emitted at large angles with respect to the beam direction (mainly protons), with the aim to reconstruct the spatial coordinates of the fragment emission point extrapolating the measured track toward the beam axis. The DP is currently under development within of the INSIDE collaboration (Innovative Solutions for In-beam Dosimetry in hadrontherapy). The tracker is made by six layers (20 × 20 cm²) of BCF-12 square scintillating fibres (500 μm) coupled to Silicon Photo-Multipliers, followed by two plastic scintillator layers of 6 mm thickness. A system of front-end boards based on FPGAs arranged around the detector provides the data acquisition. The detector characterization with cosmic rays is currently undergoing, and a data taking campaign with protons will take place in May 2017. The DP design and the performances measured with using MIPs and protons beam will be reviewed.

Keywords: fragmentation, monitoring, particle therapy, tracking

Procedia PDF Downloads 238

Authors: Easa Ali Abbasi, Akbar Allahverdizadeh, Reza Jahangiri, Behnam Dadashzadeh

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Electrical current measurement is a suitable method for the performance determination of electrical devices. There are two contact and noncontact methods in this measuring process. Contact method has some disadvantages like having direct connection with wire which may endamage the system. Thus, in this paper, a bimorph piezoelectric cantilever beam which has a permanent magnet on its free end is used to measure electrical current in a noncontact way. In mathematical modeling, based on Galerkin method, the governing equation of the cantilever beam is solved, and the equation presenting the relation between applied force and beam’s output voltage is presented. Magnetic force resulting from current carrying wire is considered as the external excitation force of the system. The results are compared with other references in order to demonstrate the accuracy of the mathematical model. Finally, the effects of geometric parameters on the output voltage and natural frequency are presented.

Keywords: cantilever beam, electrical current measurement, forced excitation, piezoelectric

Procedia PDF Downloads 236

Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

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Authors: E. Faizan, Wahab Abdul Ghafar, Tao Zhong

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Steel plate shear walls (SPSWs) are a robust lateral load resistance structure because of their high flexibility and efficient energy dissipation when subjected to seismic loads. This research investigates the seismic performance of an innovative infill web strip (IWS-SPSW) and a typical unstiffened steel plate shear wall (USPSW). As a result, two 1:3 scale specimens of an IWS-SPSW and USPSW with a single story and a single bay were built and subjected to a cyclic lateral loading methodology. In the prototype, the beam-to-column connections were accomplished with the assistance of semi-rigid end-plate connectors. IWS-SPSW demonstrated exceptional ductility and shear load-bearing capacity during the testing process, with no cracks or other damage occurring. In addition, the IWS-SPSW could effectively dissipate energy without causing a significant amount of beam-column connection distortion. The shear load-bearing capacity of the USPSW was exceptional. However, it exhibited low ductility, severe infill plate corner ripping, and huge infill web plate cracks. The FE models were created and then confirmed using the experimental data. It has been demonstrated that the infill web strips of an SPSW system can affect the system's high performance and total energy dissipation. In addition, a parametric analysis was carried out to evaluate the material qualities of the IWS, which can considerably improve the system's seismic performances. These properties include the steel's strength as well as its thickness.

Keywords: steel shear walls, seismic performance, failure mode, hysteresis response, nonlinear finite element analysis, parametric study

Procedia PDF Downloads 78

Authors: A. Hassoune, M. Khafallah, A. Mesbahi, T. Bouragba

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This work presents an improved strategy of control for charging a lithium-ion battery in an electric vehicle charging station using two charger topologies i.e. single ended primary inductor converter (SEPIC) and forward converter. In terms of rapidity and accuracy, the power system consists of a topology/control diagram that would overcome the performance constraints, for instance the power instability, the battery overloading and how the energy conversion blocks would react efficiently to any kind of perturbations. Simulation results show the effectiveness of the proposed topologies operated with a power management algorithm based on voltage/peak current mode controls. In order to provide credible findings, a low power prototype is developed to test the control strategy via experimental evaluations of the converter topology and its controls.

Keywords: battery storage buffer, charging station, electric vehicle, experimental analysis, management algorithm, switches control

Procedia PDF Downloads 169

Authors: Ranveet Saggu, Saad Bin Ahmed

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Cardiovascular Disease (CVD) is the leading cause of death worldwide. One of its main manifestations, myocardial infarction (commonly known as a heart attack), occurs about 750,000 times a year, caused by insufficient blood flow to a portion of the heart muscle. A quick and accurate diagnosis of a heart attack or heart failure is crucial in the treatment of the patient. The aim of this research project is to improve the prediction of cardiovascular diseases by automating risk assessment using binary classifiers. The methodology includes Exploratory Data Analysis (EDA), which helps to obtain information about the dataset with the help of visualizations and metrics. Additionally, Feature Engineering techniques is employed to address missing values, outliers, feature extraction, and normalizing the dataset. Subsequently, various classification machine learning algorithms are trained, and their accuracy along with other metrics are evaluated to identify the most efficient model in terms of processing time and predictive performance.

Keywords: cardiovascular disease, machine learning, deci- sion trees, logistic regression, k-nearest neighbor, xgboost, random forest, gradient boosting

Procedia PDF Downloads 14

Authors: Tamale Vincent

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Groundwater investigation is the investigation of underground formations to understand the hydrologic cycle, known groundwater occurrences, and identify the nature and types of aquifers. There are different groundwater investigation methods and surface geophysical method is one of the groundwater investigation more especially the Geoelectrical resistivity Schlumberger configuration method which provides valuable information regarding the lateral and vertical successions of subsurface geomaterials in terms of their individual thickness and corresponding resistivity values besides using surface geophysical method, hydrogeological and geological investigation methods are also incorporated to aid in preliminary groundwater investigation. Investigation for groundwater in lwantonde district has been implemented. The area project is located cattle corridor and the dry seasonal troubles the communities in lwantonde district of which 99% of people living there are farmers, thus making agriculture difficult and local government to provide social services to its people. The investigation was done using the Geoelectrical resistivity Schlumberger configuration method. The measurement point is located in the three sub-counties, with a total of 17 measurement points. The study location is at 0025S, 3110E, and covers an area of 160 square kilometers. Based on the results of the Geoelectrical information data, it was found two types of aquifers, which are open aquifers in depth ranging from six meters to twenty-two meters and a confined aquifer in depth ranging from forty-five meters to eighty meters. In addition to the Geoelectrical information data, drilling was done at an accessible point by heavy equipment in the Lwakagura village, Kabura sub-county. At the drilling point, artesian wells were obtained at a depth of eighty meters and can rise to two meters above the soil surface. The discovery of artesian well is then used by residents to meet the needs of clean water and for irrigation considering that in this area most wells contain iron content.

Keywords: artesian well, geoelectrical, lwantonde, Schlumberger

Procedia PDF Downloads 133

Authors: Fang Li, Xie-Yuan Yin, Xie-Zhen Yin

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Instability and breakup of electrified viscoelastic liquid jets are involved in various applications such as inkjet printing, fuel atomization, the pharmaceutical industry, electrospraying, and electrospinning. Studying on the instability of electrified viscoelastic liquid jets is of theoretical and practical significance. We built a one-dimensional electrified viscoelastic model to study the nonlinear instability behavior of a perfecting conducting, slightly viscoelastic liquid jet under a radial electric field. The model is solved numerically by using an implicit finite difference scheme together with a boundary element method. It is found that under a radial electric field a viscoelastic liquid jet still evolves into a beads-on-string structure with a thin filament connecting two adjacent droplets as in the absence of an electric field. A radial electric field exhibits limited influence on the decay of the filament thickness in the nonlinear evolution process of a viscoelastic jet, in contrast to its great enhancing effect on the linear instability of the jet. On the other hand, a radial electric field can induce axial non-uniformity of the first normal stress difference within the filament. Particularly, the magnitude of the first normal stress difference near the midpoint of the filament can be greatly decreased by a radial electric field. Decreasing the extensional stress by a radial electric field may found applications in spraying, spinning, liquid bridges and others. In addition, the effect of a radial electric field on the formation of satellite droplets is investigated on the parametric plane of the dimensionless wave number and the electrical Bond number. It is found that satellite droplets may be formed for a larger axial wave number at a larger radial electric field. The present study helps us gain insight into the nonlinear instability characteristics of electrified viscoelastic liquid jets.

Keywords: non linear instability, one-dimensional models, radial electric fields, viscoelastic liquid jets

Procedia PDF Downloads 394

Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

Procedia PDF Downloads 280

Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

Procedia PDF Downloads 114

Authors: Aditi Viswanathan, Shree Ranjani, Aruna Govada

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With data sizes constantly expanding, and with classical machine learning algorithms that analyze such data requiring larger and larger amounts of computation time and storage space, the need to distribute computation and memory requirements among several computers has become apparent. Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored. This research seeks to develop an algorithm that implements the Support Vector Machine over a multi-class data set and is efficient in a distributed environment. For this, we recursively choose the best binary split of a set of classes using a greedy technique. Much like the divide and conquer approach. Our algorithm has shown better computation time during the testing phase than the traditional sequential SVM methods (One vs. One, One vs. Rest) and out-performs them as the size of the data set grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.

Keywords: distributed algorithm, MapReduce, multi-class, support vector machine

Procedia PDF Downloads 405

Authors: Hanan Alsaeid Alshenawy

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Background: Cervical dysplasia, which is potentially precancerous, has increased in young women. Detection of cervical is important for reducing morbidity and mortality in cervical cancer. This study analyzes the immunohistochemical expression of p16, HPV L1 capsid protein and Ki67 in cervical intraepithelial lesions and correlates them with lesion grade to develop a set of markers for diagnosis and detect the prognosis of cervical cancer precursors. Methods: 75 specimens were analyzed including 15 cases CIN 1, 28 CIN 2, 20 CIN 3, and 12 cervical squamous carcinoma, besides 10 normal cervical tissues. They were stained for p16, HPV L1 and Ki-67. Sensitivity, specificity, predictive values and accuracy were evaluated for each marker. Results: p16 expression increased during the progression from CIN 1 to carcinoma. HPV L1 positivity was detected in CIN 2 and decreased gradually as the CIN grade increased but disappear in carcinoma. Strong Ki-67 expression was observed with high grades CIN and carcinoma. p16, HPV L1 and Ki67 were sensitive but with variable specificity in detecting CIN lesions. Conclusions: p16, HPV L1 and Ki67 are useful set of markers in establishing the risk of high-grade CIN. They complete each other to reach accurate diagnosis and prognosis.

Keywords: p16, HPV L1, Ki67, CIN, cervical carcinoma

Procedia PDF Downloads 344

Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

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No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

Procedia PDF Downloads 299

Authors: Saba. T. Suliman, Alaa. H. Osman, Sara. T. Ahmed, Zeinab. A. Mustafa, Akram. I. Omara, Banazier. A. Ibraheem

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Diagnosis by sweat is one of the emerging methods whereby sweat can identify many diseases in the human body. Sweat contains many elements that help in the diagnostic process. In this research, we analyzed sweat samples by using a Colorimeter device to identify the disease of kidney failure in its various stages. This analysis is a non-invasive method where the sample is collected from outside the body, and then this sample is analyzed. Urea refers to the disease of kidney failure when its quantity is high in the blood and then in the sweat, and by experience, we found that the amount of urea for males differs from its quantity for females, where there is a noticeable increase for males in normal and pathological cases. In this research, we took many samples from a normal group that does not suffer from renal failure and another who suffers from the disease to compare the percentage of urea, and after analysis, we found that the urea percentage is high in people with kidney failure disease. with an accuracy of results of 85%.

Keywords: sweat analysis, kidney failure, urea, non-invasive, eccrine glands, mineral composition, sweat test

Procedia PDF Downloads 47

Authors: Byung Cheol Kim

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The Program Evaluation and Review Technique (PERT) is widely used for project management, but it struggles with subjective distributions, particularly due to its assumptions of constant variance and light tails. To overcome these limitations, we propose the Generalized PERT (G-PERT) model, which enhances PERT by incorporating variability in three-point subjective estimates. Our methodology extends the original PERT model to cover the full range of unimodal beta distributions, enabling the model to handle thick-tailed distributions and offering formulas for computing mean and variance. This maintains the simplicity of PERT while providing a more accurate depiction of uncertainty. Our empirical analysis demonstrates that the G-PERT model significantly improves performance, particularly when dealing with heavy-tail subjective distributions. In comparative assessments with alternative models such as triangular and lognormal distributions, G-PERT shows superior accuracy and flexibility. These results suggest that G-PERT offers a more robust solution for project estimation while still retaining the user-friendliness of the classic PERT approach.

Keywords: PERT, subjective distribution, project management, flexible variance

Procedia PDF Downloads 24

Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

Procedia PDF Downloads 117

Authors: Akram Boubakri, Fethi Choubani, Tan Hoa Vuong, Jacques David

Abstract:

Nowadays, microwave hyperthermia is considered as an effective treatment for the malignant tumors. This microwave treatment which comes to substitute the chemotherapy and the surgical intervention enables an in-depth tumor heating without causing any diseases to the sane tissue. This technique requires a high precision system, in order to effectively concentrate the heating just in the tumor, without heating any surrounding healthy tissue. In the hyperthermia treatment, the temperature in cancerous area is typically raised up to over 42◦C and maintained for one hour in order to destroy the tumor sufficiently, whilst in the surrounding healthy tissues, the temperature is maintained below 42◦C to avoid any damage. Metamaterial lenses are widely used in medical applications like microwave hyperthermia treatment. They enabled a subdiffraction resolution thanks to the amplification of the evanescent waves and they can focus electromagnetic waves from a point source to a point image. Metasurfaces have been used to built metamaterial lenses. The main mechanical advantages of those structures over three dimensional material structures are ease of fabrication and a smaller required volume. Here in this work, we proposed a metasurface based lens operating at the frequency of 6 GHz and designed for microwave hyperthermia. This lens was applied and showed good results in focusing and heating the tumor inside a breast tissue with an increased and maintained temperature above 42°C. The tumor was placed in the focal distance of the lens so that only the tumor tissue will be heated. Finally, in this work, it has been shown that the hyperthermia area within the tissue can be carefully adjusted by moving the antennas or by changing the thickness of the metamaterial lenses based on the tumor position. Even though the simulations performed in this work have taken into account an ideal case, some real characteristics can be considered to improve the obtained results in a realistic model.

Keywords: focusing, hyperthermia, metamaterial lenses, metasurface, microwave treatment

Procedia PDF Downloads 233

Authors: Gabrielle Holt

Abstract:

This paper is looking to prove the efficacy of the Schulte Holt IOL Toric Calculator Processor (Schulte Holt ITCP). It has been completed using manually inputted data into the Barrett Toric Calculator and comparing the number of minutes taken to complete the Toric calculations, the number of errors identified during completion, and distractions during completion. It will then compare that data to the number of minutes taken for the Schulte Holt ITCP to complete also, using the Barrett method, as well as the number of errors identified in the Schulte Holt ITCP. The data clearly demonstrate a momentous advantage to the Schulte Holt ITCP and notably reduces time spent doing Toric Calculations, as well as reducing the number of errors. With the ever-growing number of cataract surgeries taking place around the world and the waitlists increasing -the Schulte Holt IOL Toric Calculator Processor may well demonstrate a way forward to increase the availability of ophthalmologists and ophthalmic staff while maintaining patient safety.

Keywords: Toric, toric lenses, ophthalmology, cataract surgery, toric calculations, Barrett

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

Procedia PDF Downloads 278

Authors: Pabitra Sahu, M. Manohari, S. Priyadharshini, R. Santhanam, S. Chandrasekaran, B. Venkatraman

Abstract:

Radiation workers of reprocessing plants have a potential for internal exposure due to actinides and fission products. Radionuclides like Americium, lead, Polonium and Europium are bone seekers and get accumulated in the skeletal part. As the major skeletal content is in the skull (13%) and knee (22%), measurements of old intake have to be carried out in the skull and knee. At the Indira Gandhi Centre for Atomic Research, a twin HPGe-based actinide monitor is used for the measurement of actinides present in bone. Efficiency estimation, which is one of the prerequisites for the quantification of radionuclides, requires anthropomorphic phantoms. Such phantoms are very limited. Hence, in this study, efficiency curves for a Twin HPGe-based actinide monitoring system are established theoretically using the FLUKA Monte Carlo method and ICRP adult male voxel phantom. In the case of skull measurement, the detector is placed over the forehead, and for knee measurement, one detector is placed over each knee. The efficiency values of radionuclides present in the knee and skull vary from 3.72E-04 to 4.19E-04 CPS/photon and 5.22E-04 to 7.07E-04 CPS/photon, respectively, for the energy range 17 to 3000keV. The efficiency curves for the measurement are established, and it is found that initially, the efficiency value increases up to 100 keV and then starts decreasing. It is found that the skull efficiency values are 4% to 63% higher than that of the knee, depending on the energy for all the energies except 17.74 keV. The reason is the closeness of the detector to the skull compared to the knee. But for 17.74 keV the efficiency of the knee is more than the skull due to the higher attenuation caused in the skull bones because of its greater thickness. The Minimum Detectable Activity (MDA) for 241Am present in the skull and knee is 9 Bq. 239Pu has a MDA of 950 Bq and 1270 Bq for knee and skull, respectively, for a counting time of 1800 sec. This paper discusses the simulation method and the results obtained in the study.

Keywords: FLUKA Monte Carlo Method, ICRP adult male voxel phantom, knee, Skull.

Procedia PDF Downloads 55