Search results for: edge detection algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7073

Search results for: edge detection algorithm

2183 Influence of Geometrical Parameters of a Wind Turbine on the Optimal Tip-Speed Ratio

Authors: Zdzislaw Piotr Kaminski, Miroslaw Wendeker, Zbigniew Czyz

Abstract:

The paper describes the geometric model, calculation algorithm and results of the CFD simulation of the airflow around a rotor in the vertical axis wind turbine (VAWT) with the ANSYS Fluent computational solver. The CFD method enables creating aerodynamic characteristics of forces acting on rotor working surfaces and determining parameters such as torque or power generated by the rotor assembly. The object of the research was a rotor whose construction is based on patent no.PL219985. The conducted tests enabled a mathematical model with a description of the generation of aerodynamic forces acting on each rotor blade. Additionally, this model was compared to the results of the wind tunnel tests. The analysis also focused on the influence of the blade angle on turbine power and the TSR. The research has shown that the turbine blade angle has a significant impact on the optimal value of the TSR.

Keywords: computational fluid dynamics, numerical analysis, renewable energy, wind turbine

Procedia PDF Downloads 144
2182 Determination of Nanomolar Mercury (II) by Using Multi-Walled Carbon Nanotubes Modified Carbon Zinc/Aluminum Layered Double Hydroxide – 3 (4-Methoxyphenyl) Propionate Nanocomposite Paste Electrode

Authors: Illyas Md Isa, Sharifah Norain Mohd Sharif, Norhayati Hashima

Abstract:

A mercury(II) sensor was developed by using multi-walled carbon nanotubes (MWCNTs) paste electrode modified with Zn/Al layered double hydroxide-3(4-methoxyphenyl)propionate nanocomposite (Zn/Al-HMPP). The optimum conditions by cyclic voltammetry were observed at electrode composition 2.5% (w/w) of Zn/Al-HMPP/MWCNTs, 0.4 M potassium chloride, pH 4.0, and scan rate of 100 mVs-1. The sensor exhibited wide linear range from 1x10-3 M to 1x10-7 M Hg2+ and 1x10-7 M to 1x10-9 M Hg2+, with a detection limit of 1x10-10 M Hg2+. The high sensitivity of the proposed electrode towards Hg(II) was confirmed by double potential-step chronocoulometry which indicated these values; diffusion coefficient 1.5445 x 10-9 cm2 s-1, surface charge 524.5 µC s-½ and surface coverage 4.41 x 10-2 mol cm-2. The presence of 25-fold concentration of most metal ions had no influence on the anodic peak current. With characteristics such as high sensitivity, selectivity and repeatability the electrode was then proposed as the appropriate alternative for the determination of mercury(II).

Keywords: cyclic voltammetry, mercury(II), modified carbon paste electrode, nanocomposite

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2181 A 15 Minute-Based Approach for Berth Allocation and Quay Crane Assignment

Authors: Hoi-Lam Ma, Sai-Ho Chung

Abstract:

In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment

Procedia PDF Downloads 161
2180 Absorbed Dose Estimation of 68Ga-EDTMP in Human Organs

Authors: S. Zolghadri, H. Yousefnia, A. R. Jalilian

Abstract:

Bone metastases are observed in a wide range of cancers leading to intolerable pain. While early detection can help the physicians in the decision of the type of treatment, various radiopharmaceuticals using phosphonates like 68Ga-EDTMP have been developed. In this work, due to the importance of absorbed dose, human absorbed dose of this new agent was calculated for the first time based on biodistribution data in Wild-type rats. 68Ga was obtained from 68Ge/68Ga generator with radionuclidic purity and radiochemical purity of higher than 99%. The radiolabeled complex was prepared in the optimized conditions. Radiochemical purity of the radiolabeled complex was checked by instant thin layer chromatography (ITLC) method using Whatman No. 2 paper and saline. The results indicated the radiochemical purity of higher than 99%. The radiolabelled complex was injected into the Wild-type rats and its biodistribution was studied up to 120 min. As expected, major accumulation was observed in the bone. Absorbed dose of each human organ was calculated based on biodistribution in the rats using RADAR method. Bone surface and bone marrow with 0.112 and 0.053 mSv/MBq, respectively, received the highest absorbed dose. According to these results, the radiolabeled complex is a suitable and safe option for PET bone imaging.

Keywords: absorbed dose, EDTMP, ⁶⁸Ga, rats

Procedia PDF Downloads 191
2179 WSN System Warns Atta Cephalotes Climbing in Mango Fruit Trees

Authors: Federico Hahn Schlam, Fermín Martínez Solís

Abstract:

Leaf-cutting ants (Atta cephalotes) forage from mango tree leaves and flowers to feed their colony. Farmers find it difficult to control ants due to the great quantity of trees grown in commercial orchards. In this article, IoT can support farmers for ant detection in real time, as production losses can be considered of 324 US per tree.A wireless sensor network, WSN, was developed to warn the farmer from ant presence in trees during a night. Mango trees were gathered into groups of 9 trees, where the central tree holds the master microcontroller, and the other eight trees presented slave microcontrollers (nodes). At each node, anemitter diode-photodiode unitdetects ants climbing up. A capacitor is chargedand discharged after being sampled every ten minutes. The system usesBLE (Bluetooth Low Energy) to communicate between the master microcontroller by BLE.When ants were detected the number of the tree was transmitted via LoRa from the masterto the producer smartphone to warn him. In this paper, BLE, LoRa, and energy consumption were studied under variable vegetation in the orchard. During 2018, 19 trees were attacked by ants, and ants fed 26.3% of flowers and 73.7% of leaves.

Keywords: BLE, atta cephalotes, LoRa, WSN-smartphone, energy consumption

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2178 Regulatory and Economic Challenges of AI Integration in Cyber Insurance

Authors: Shreyas Kumar, Mili Shangari

Abstract:

Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

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2177 3D Simulation of Orthodontic Tooth Movement in the Presence of Horizontal Bone Loss

Authors: Azin Zargham, Gholamreza Rouhi, Allahyar Geramy

Abstract:

One of the most prevalent types of alveolar bone loss is horizontal bone loss (HBL) in which the bone height around teeth is reduced homogenously. In the presence of HBL the magnitudes of forces during orthodontic treatment should be altered according to the degree of HBL, in a way that without further bone loss, desired tooth movement can be obtained. In order to investigate the appropriate orthodontic force system in the presence of HBL, a three-dimensional numerical model capable of the simulation of orthodontic tooth movement was developed. The main goal of this research was to evaluate the effect of different degrees of HBL on a long-term orthodontic tooth movement. Moreover, the effect of different force magnitudes on orthodontic tooth movement in the presence of HBL was studied. Five three-dimensional finite element models of a maxillary lateral incisor with 0 mm, 1.5 mm, 3 mm, 4.5 mm and 6 mm of HBL were constructed. The long-term orthodontic tooth tipping movements were attained during a 4-weeks period in an iterative process through the external remodeling of the alveolar bone based on strains in periodontal ligament as the bone remodeling mechanical stimulus. To obtain long-term orthodontic tooth movement in each iteration, first the strains in periodontal ligament under a 1-N tipping force were calculated using finite element analysis. Then, bone remodeling and the subsequent tooth movement were computed in a post-processing software using a custom written program. Incisal edge, cervical, and apical area displacement in the models with different alveolar bone heights (0, 1.5, 3, 4.5, 6 mm bone loss) in response to a 1-N tipping force were calculated. Maximum tooth displacement was found to be 2.65 mm at the top of the crown of the model with a 6 mm bone loss. Minimum tooth displacement was 0.45 mm at the cervical level of the model with a normal bone support. Tooth tipping degrees of models in response to different tipping force magnitudes were also calculated for models with different degrees of HBL. Degrees of tipping tooth movement increased as force level was increased. This increase was more prominent in the models with smaller degrees of HBL. By using finite element method and bone remodeling theories, this study indicated that in the presence of HBL, under the same load, long-term orthodontic tooth movement will increase. The simulation also revealed that even though tooth movement increases with increasing the force, this increase was only prominent in the models with smaller degrees of HBL, and tooth models with greater degrees of HBL will be less affected by the magnitude of an orthodontic force. Based on our results, the applied force magnitude must be reduced in proportion of degree of HBL.

Keywords: bone remodeling, finite element method, horizontal bone loss, orthodontic tooth movement.

Procedia PDF Downloads 335
2176 Optimization of Machining Parametric Study on Electrical Discharge Machining

Authors: Rakesh Prajapati, Purvik Patel, Hardik Patel

Abstract:

Productivity and quality are two important aspects that have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process, as well as the product developed. The electrical discharge machining (EDM) process, even now it is an experience process, wherein the selected parameters are still often far from the maximum, and at the same time selecting optimization parameters is costly and time consuming. Material Removal Rate (MRR) during the process has been considered as a productivity estimate with the aim to maximize it, with an intention of minimizing surface roughness taken as most important output parameter. These two opposites in nature requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Regression Analysis and Analysis of Variance. Then objective function is optimized using Genetic Algorithm technique. The model is shown to be effective; MRR and Surface Roughness improved using optimized machining parameters.

Keywords: MMR, TWR, OC, DOE, ANOVA, minitab

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2175 The Use of SD Bioline TB AgMPT64® Detection Assay for Rapid Characterization of Mycobacteria in Nigeria

Authors: S. Ibrahim, U. B. Abubakar, S. Danbirni, A. Usman, F. M. Ballah, C. A. Kudi, L. Lawson, G. H. Abdulrazak, I. A. Abdulkadir

Abstract:

Performing culture and characterization of mycobacteria in low resource settings like Nigeria is a very difficult task to undertake because of the very few and limited laboratories carrying out such an experiment; this is a largely due to stringent and laborious nature of the tests. Hence, a rapid, simple and accurate test for characterization is needed. The “SD BIOLINE TB Ag MPT 64 Rapid ®” is a simple and rapid immunochromatographic test used in differentiating Mycobacteria into Mycobacterium tuberculosis (NTM). The 100 sputa were obtained from patients suspected to be infected with tuberculosis and presented themselves to hospitals for check-up and treatment were involved in the study. The samples were cultured in a class III Biosafety cabinet and level III biosafety practices were followed. Forty isolates were obtained from the cultured sputa, and there were identified as Acid-fast bacilli (AFB) using Zeihl-Neelsen acid-fast stain. All the isolates (AFB positive) were then subjected to the SD BIOLINE Analyses. A total of 31 (77.5%) were characterized as MTBC, while nine (22.5%) were NTM. The total turnaround time for the rapid assay was just 30 minutes as compared to a few days of phenotypic and genotypic method. It was simple, rapid and reliable test to differentiate MTBC from NTM.

Keywords: culture, mycobacteria, non tuberculous mycobacterium, SD Bioline

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2174 Forensic Analysis of Thumbnail Images in Windows 10

Authors: George Kurian, Hongmei Chi

Abstract:

Digital evidence plays a critical role in most legal investigations. In many cases, thumbnail databases show important information in that investigation. The probability of having digital evidence retrieved from a computer or smart device has increased, even though the previous user removed data and deleted apps on those devices. Due to the increase in digital forensics, the ability to store residual information from various thumbnail applications has improved. This paper will focus on investigating thumbnail information from Windows 10. Thumbnail images of interest in forensic investigations may be intact even when the original pictures have been deleted. It is our research goal to recover useful information from thumbnails. In this research project, we use various forensics tools to collect left thumbnail information from deleted videos or pictures. We examine and describe the various thumbnail sources in Windows and propose a methodology for thumbnail collection and analysis from laptops or desktops. A machine learning algorithm is adopted to help speed up content from thumbnail pictures.

Keywords: digital forensic, forensic tools, soundness, thumbnail, machine learning, OCR

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2173 Image Compression Based on Regression SVM and Biorthogonal Wavelets

Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

Abstract:

In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

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2172 Design and Implementation of an AI-Enabled Task Assistance and Management System

Authors: Arun Prasad Jaganathan

Abstract:

In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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2171 3D Quantum Simulation of a HEMT Device Performance

Authors: Z. Kourdi, B. Bouazza, M. Khaouani, A. Guen-Bouazza, Z. Djennati, A. Boursali

Abstract:

We present a simulation of a HEMT (high electron mobility transistor) structure with and without a field plate. We extract the device characteristics through the analysis of DC, AC and high frequency regimes, as shown in this paper. This work demonstrates the optimal device with a gate length of 15 nm, InAlN/GaN heterostructure and field plate structure, making it superior to modern HEMTs when compared with otherwise equivalent devices. This improves the ability to bear the burden of the current density passes in the channel. We have demonstrated an excellent current density, as high as 2.05 A/mm, a peak extrinsic transconductance of 590 mS/mm at VDS=2 V, and cutting frequency cutoffs of 638 GHz in the first HEMT and 463 GHz for Field plate HEMT., maximum frequency of 1.7 THz, maximum efficiency of 73%, maximum breakdown voltage of 400 V, DIBL=33.52 mV/V and an ON/OFF current density ratio higher than 1 x 1010. These values were determined through the simulation by deriving genetic and Monte Carlo algorithms that optimize the design and the future of this technology.

Keywords: HEMT, Silvaco, field plate, genetic algorithm, quantum

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2170 Sentence Structure for Free Word Order Languages in Context with Anaphora Resolution: A Case Study of Hindi

Authors: Pardeep Singh, Kamlesh Dutta

Abstract:

Many languages have fixed sentence structure and others are free word order. The accuracy of anaphora resolution of syntax based algorithm depends on structure of the sentence. So, it is important to analyze the structure of any language before implementing these algorithms. In this study, we analyzed the sentence structure exploiting the case marker in Hindi as well as some special tag for subject and object. We also investigated the word order for Hindi. Word order typology refers to the study of the order of the syntactic constituents of a language. We analyzed 165 news items of Ranchi Express from EMILEE corpus of plain text. It consisted of 1745 sentences. Eight file of dialogue based from the same corpus has been analyzed which will have 1521 sentences. The percentages of subject object verb structure (SOV) and object subject verb (OSV) are 66.90 and 33.10, respectively.

Keywords: anaphora resolution, free word order languages, SOV, OSV

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2169 Knowledge of Pap Smear Test and Visual Inspection with Acetic Acid in Cervical Cancer Patients in Manado

Authors: Eric Ng, Freddy W. Wagey, Frank M. M. Wagey

Abstract:

Background: Cervical cancer is the fourth most common cancer in women worldwide and the most common cancer in many low- and middle-income countries. The main causes are the lack of prevention programs and effective therapy, as well as the lack of knowledge about cervical cancer and awareness for early detection. The Pap smear test and visual inspection with acetic acid (VIA) allow the cervical lesion to be detected so that progression to cervical cancer can be avoided. Objective: The purpose of this study was to evaluate the knowledge of Pap smear test and VIA in cervical cancer patients. Methodology: A total of 67 cervical cancer patients in Manado who volunteered to participate in the research were identified as the sample. The data were collected during the month of November 2019-January 2020 with a questionnaire about the respondents' knowledge relating to Pap smear test and VIA. Questionnaire data were analysed using descriptive statistics. Results: Knowledge of pap smear among cervical cancer patients were good in 9 respondents (13.4%), moderate in 20 respondents (29.9%), and bad in 38 respondents (56.7%), whereas the knowledge of VIA was good in 13 respondents (19.4%), moderate in 15 respondents (22.4%), and bad in 39 respondents (58.2%). Conclusion: Majority of cervical cancer patients in Manado still had bad knowledge about Pap smear tests and VIA.

Keywords: cervical cancer, knowledge, pap smear test, visual inspection with acetic acid

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2168 Study of Durability of Porous Polymer Materials, Glass-Fiber-Reinforced Polyurethane Foam (R-PUF) in MarkIII Containment Membrane System

Authors: Florent Cerdan, Anne-Gaëlle Denay, Annette Roy, Jean-Claude Grandidier, Éric Laine

Abstract:

The insulation of MarkIII membrane of the Liquid Natural Gas Carriers (LNGC) consists of a load- bearing system made of panels in reinforced polyurethane foam (R-PUF). During the shipping, the cargo containment shall be potentially subject to risk events which can be water leakage through the wall ballast tank. The aim of these present works is to further develop understanding of water transfer mechanisms and water effect on properties of R-PUF. This multi-scale approach contributes to improve the durability. Macroscale / Mesoscale Firstly, the use of the gravimetric technique has allowed to define, at room temperature, the water transfer mechanisms and kinetic diffusion, in the R-PUF. The solubility follows a first kinetic fast growing connected to the water absorption by the micro-porosity, and then evolves linearly slowly, this second stage is connected to molecular diffusion and dissolution of water in the dense membranes polyurethane. Secondly, in the purpose of improving the understanding of the transfer mechanism, the study of the evolution of the buoyant force has been established. It allowed to identify the effect of the balance of total and partial pressure of mixture gas contained in pores surface. Mesoscale / Microscale The differential scanning calorimetry (DSC) and Dynamical Mechanical Analysis (DMA), have been used to investigate the hydration of the hard and soft segments of the polyurethane matrix. The purpose was to identify the sensitivity of these two phases. It been shown that the glass transition temperatures shifts towards the low temperatures when the solubility of the water increases. These observations permit to conclude to a plasticization of the polymer matrix. Microscale The Fourier Transform Infrared (FTIR) study has been used to investigate the characterization of functional groups on the edge, the center and mid-way of the sample according the duration of submersion. More water there is in the material, more the water fix themselves on the urethanes groups and more specifically on amide groups. The pic of C=O urethane shifts at lower frequencies quickly before 24 hours of submersion then grows slowly. The intensity of the pic decreases more flatly after that.

Keywords: porous materials, water sorption, glass transition temperature, DSC, DMA, FTIR, transfer mechanisms

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2167 Cotton Crops Vegetative Indices Based Assessment Using Multispectral Images

Authors: Muhammad Shahzad Shifa, Amna Shifa, Muhammad Omar, Aamir Shahzad, Rahmat Ali Khan

Abstract:

Many applications of remote sensing to vegetation and crop response depend on spectral properties of individual leaves and plants. Vegetation indices are usually determined to estimate crop biophysical parameters like crop canopies and crop leaf area indices with the help of remote sensing. Cotton crops assessment is performed with the help of vegetative indices. Remotely sensed images from an optical multispectral radiometer MSR5 are used in this study. The interpretation is based on the fact that different materials reflect and absorb light differently at different wavelengths. Non-normalized and normalized forms of these datasets are analyzed using two complementary data mining algorithms; K-means and K-nearest neighbor (KNN). Our analysis shows that the use of normalized reflectance data and vegetative indices are suitable for an automated assessment and decision making.

Keywords: cotton, condition assessment, KNN algorithm, clustering, MSR5, vegetation indices

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2166 Credit Risk Evaluation Using Genetic Programming

Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

Abstract:

Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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2165 AM/E/c Queuing Hub Maximal Covering Location Model with Fuzzy Parameter

Authors: M. H. Fazel Zarandi, N. Moshahedi

Abstract:

The hub location problem appears in a variety of applications such as medical centers, firefighting facilities, cargo delivery systems and telecommunication network design. The location of service centers has a strong influence on the congestion at each of them, and, consequently, on the quality of service. This paper presents a fuzzy maximal hub covering location problem (FMCHLP) in which travel costs between any pair of nodes is considered as a fuzzy variable. In order to consider the quality of service, we model each hub as a queue. Arrival rate follows Poisson distribution and service rate follows Erlang distribution. In this paper, at first, a nonlinear mathematical programming model is presented. Then, we convert it to the linear one. We solved the linear model using GAMS software up to 25 nodes and for large sizes due to the complexity of hub covering location problems, and simulated annealing algorithm is developed to solve and test the model. Also, we used possibilistic c-means clustering method in order to find an initial solution.

Keywords: fuzzy modeling, location, possibilistic clustering, queuing

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2164 Numerical Investigation on the Influence of Incoming Flow Conditions on the Rotating Stall in Centrifugal Pump

Authors: Wanru Huang, Fujun Wang, Chaoyue Wang, Yuan Tang, Zhifeng Yao, Ruofu Xiao, Xin Chen

Abstract:

Rotating stall in centrifugal pump is an unsteady flow phenomenon that causes instabilities and high hydraulic losses. It typically occurs at low flow rates due to large flow separation in impeller blade passage. In order to reveal the influence of incoming flow conditions on rotating stall in centrifugal pump, a numerical method for investigating rotating stall was established. This method is based on a modified SST k-ω turbulence model and a fine mesh model was adopted. The calculated flow velocity in impeller by this method was in good agreement with PIV results. The effects of flow rate and sealing-ring leakage on stall characteristics of centrifugal pump were studied by using the proposed numerical approach. The flow structures in impeller under typical flow rates and typical sealing-ring leakages were analyzed. It is found that the stall vortex frequency and circumferential propagation velocity increase as flow rate decreases. With the flow rate decreases from 0.40Qd to 0.30Qd, the stall vortex frequency increases from 1.50Hz to 2.34Hz, the circumferential propagation velocity of the stall vortex increases from 3.14rad/s to 4.90rad/s. Under almost all flow rate conditions where rotating stall is present, there is low frequency of pressure pulsation between 0Hz-5Hz. The corresponding pressure pulsation amplitude increases with flow rate decreases. Taking the measuring point at the leading edge of the blade pressure surface as an example, the flow rate decreases from 0.40Qd to 0.30Qd, the pressure fluctuation amplitude increases by 86.9%. With the increase of leakage, the flow structure in the impeller becomes more complex, and the 8-shaped stall vortex is no longer stable. On the basis of the 8-shaped stall vortex, new vortex nuclei are constantly generated and fused with the original vortex nuclei under large leakage. The upstream and downstream vortex structures of the 8-shaped stall vortex have different degrees of swimming in the flow passage, and the downstream vortex swimming is more obvious. The results show that the proposed numerical approach could capture the detail vortex characteristics, and the incoming flow conditions have significant effects on the stall vortex in centrifugal pumps.

Keywords: centrifugal pump, rotating stall, numerical simulation, flow condition, vortex frequency

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2163 Utilization of Secure Wireless Networks as Environment for Learning and Teaching in Higher Education

Authors: Mohammed A. M. Ibrahim

Abstract:

This paper investigate the utilization of wire and wireless networks to be platform for distributed educational monitoring system. Universities in developing countries suffer from a lot of shortages(staff, equipment, and finical budget) and optimal utilization of the wire and wireless network, so universities can mitigate some of the mentioned problems and avoid the problems that maybe humble the education processes in many universities by using our implementation of the examinations system as a test-bed to utilize the network as a solution to the shortages for academic staff in Taiz University. This paper selects a two areas first one quizzes activities is only a test bed application for wireless network learning environment system to be distributed among students. Second area is the features and the security of wireless, our tested application implemented in a promising area which is the use of WLAN in higher education for leering environment.

Keywords: networking wire and wireless technology, wireless network security, distributed computing, algorithm, encryption and decryption

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2162 Daye™ Tampon as a Tool for Vaginal Sample Collection Towards the Detection of Genital Infections

Authors: Valentina Milanova, Kalina Mihaylova, Iva Lazarova

Abstract:

The mechanisms by which female genital infections are detected are varied and include clinician-collected high vaginal swabs, clinician-collected endocervical swabs, patient-collected vaginal swabs, and first-pass urine samples. Vaginal health screening has chronically low rates of uptake. This highlights the unmet need for a screening tool with comparable diagnostic accuracy which is familiar, convenient and easy to use for people. The Daye™ medical grade tampon offers an alternative to traditional sampling methods with the potential of increasing screening uptake among people previously too embarrassed or busy to attend gynecological appointments. In this white paper, the results of stability studies and a comparative clinical trial are discussed to assess the suitability of the device for the collection of vaginal samples for various clinical assessments. The tampon has demonstrated good sample stability and comparable sample quality compared to a self-collected vaginal swab and a clinician-collected cervical swab.

Keywords: vaginal microbiome, vaginal infections, gynaecological infections, female health, menstrual tampons, in vitro diagnostics

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2161 Application of Artificial Neural Network in Assessing Fill Slope Stability

Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

Abstract:

This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

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2160 Assessment of Exploitation Vulnerability of Quantum Communication Systems with Phase Encryption

Authors: Vladimir V. Nikulin, Bekmurza H. Aitchanov, Olimzhon A. Baimuratov

Abstract:

Quantum communication technology takes advantage of the intrinsic properties of laser carriers, such as very high data rates and low power requirements, to offer unprecedented data security. Quantum processes at the physical layer of encryption are used for signal encryption with very competitive performance characteristics. The ultimate range of applications for QC systems spans from fiber-based to free-space links and from secure banking operations to mobile airborne and space-borne networking where they are subjected to channel distortions. Under practical conditions, the channel can alter the optical wave front characteristics, including its phase. In addition, phase noise of the communication source and photo-detection noises alter the signal to bring additional ambiguity into the measurement process. If quantized values of photons are used to encrypt the signal, exploitation of quantum communication links becomes extremely difficult. In this paper, we present the results of analysis and simulation studies of the effects of noise on phase estimation for quantum systems with different number of encryption bases and operating at different power levels.

Keywords: encryption, phase distortion, quantum communication, quantum noise

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2159 Effect of CuO, Al₂O₃ and ZnO Nanoparticles on the Response Time for Natural Convection

Authors: Mefteh Bouhalleb

Abstract:

With the recent progress in nanotechnology, nanofluids have excellent potentiality in many modern engineering processes, particularly for solar systems such as concentrated solar power plants (CSP). In this context, a numerical simulation is performed to investigate laminar natural convection nanofluids in an inclined rectangular enclosure. Mass conservation, momentum, and energy equations are numerically solved by the finite volume element method using the SIMPLER algorithm for pressure-velocity coupling. In this work, we tested the acting factors on the system response time, such as the particle volume fraction of nanoparticles, particle material, particle size, an inclination angle of enclosure and Rayleigh number. The results show that the diameter of solid particles and Rayleigh number plays an important role in the system response time. The orientation angle of the cavity affects the system response time. A phenomenon of hysteresis appears when the system does not return to its initial state.

Keywords: nanofluid, nanoparticles, heat transfer, time response

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2158 Using Data Mining Technique for Scholarship Disbursement

Authors: J. K. Alhassan, S. A. Lawal

Abstract:

This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

Procedia PDF Downloads 358
2157 A Survey of Recognizing of Daily Living Activities in Multi-User Smart Home Environments

Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

Abstract:

The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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2156 Structural Health Monitoring and Damage Structural Identification Using Dynamic Response

Authors: Reza Behboodian

Abstract:

Monitoring the structural health and diagnosing their damage in the early stages has always been one of the topics of concern. Nowadays, research on structural damage detection methods based on vibration analysis is very extensive. Moreover, these methods can be used as methods of permanent and timely inspection of structures and prevent further damage to structures. Non-destructive methods are the low-cost and economical methods for determining the damage of structures. In this research, a non-destructive method for detecting and identifying the failure location in structures based on dynamic responses resulting from time history analysis is proposed. When the structure is damaged due to the reduction of stiffness, and due to the applied loads, the displacements in different parts of the structure were increased. In the proposed method, the damage position is determined based on the calculation of the strain energy difference in each member of the damaged structure and the healthy structure at any time. Defective members of the structure are indicated by the amount of strain energy relative to the healthy state. The results indicated that the proper accuracy and performance of the proposed method for identifying failure in structures.

Keywords: failure, time history analysis, dynamic response, strain energy

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2155 CFD Modeling and Optimization of Gas Cyclone Separator for Performance Improvement

Authors: N. Beit Saeid

Abstract:

Cyclones are used in the field of air industrial gases pollution and control the pollution with centrifugal forces that is generated with spatial geometry of the cyclone. Their simple design, low capital and maintenance costs and adaptability to a wide range of operating conditions have made cyclones one of the most widely used industrial dust collectors. Their cost of operation is proportional to the fan energy required to overcome their pressure drop. Optimized geometry of outlet diffuser of the cyclones potentially could reduce exit pressure losses without affecting collection efficiency. Three rectangular outlets and a radial outlet with a variable opening had been analyzed on two cyclones. Pressure drop was investigated for inlet velocities from about 10 to 20 m s−1. The radial outlet reduced cyclone pressure drop by between 8.7 and 11.9 percent when its exit area was equal to the flow area of the cyclone vortex finder or gas exit. A simple payback based on avoided energy costs was estimated to be between 3600 and 5000 h, not including installation cost.

Keywords: cyclone, CFD, optimization, genetic algorithm

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2154 Use of Fabric Phase Sorptive Extraction with Gas Chromatography-Mass Spectrometry for the Determination of Organochlorine Pesticides in Various Aqueous and Juice Samples

Authors: Ramandeep Kaur, Ashok Kumar Malik

Abstract:

Fabric Phase Sorptive Extraction (FPSE) combined with Gas chromatography Mass Spectrometry (GCMS) has been developed for the determination of nineteen organochlorine pesticides in various aqueous samples. The method consolidates the features of sol-gel derived microextraction sorbents with rich surface chemistry of cellulose fabric substrate which could directly extract sample from complex sample matrices and incredibly improve the operation with decreased pretreatment time. Some vital parameters such as kind and volume of extraction solvent and extraction time were examinedand optimized. Calibration curves were obtained in the concentration range 0.5-500 ng/mL. Under the optimum conditions, the limits of detection (LODs) were in the range 0.033 ng/mL to 0.136 ng/mL. The relative standard deviations (RSDs) for extraction of 10 ng/mL 0f OCPs were less than 10%. The developed method has been applied for the quantification of these compounds in aqueous and fruit juice samples. The results obtained proved the present method to be rapid and feasible for the determination of organochlorine pesticides in aqueous samples.

Keywords: fabric phase sorptive extraction, gas chromatography-mass spectrometry, organochlorine pesticides, sample pretreatment

Procedia PDF Downloads 473