Search results for: forecasting accuracy

Authors: Marzieh Jafarzadeh, Fatemeh Rezaee

Abstract:

Introduction: The effect of ionizing radiation on human health can be effective for genomic integrity and cell viability. It also increases the risk of cancer and malignancy. Therefore, X-ray behavior and absorption dose calculation are considered. One of the applicable tools for calculating and evaluating the absorption dose in human tissues is Monte Carlo simulation. Monte Carlo offers a straightforward way to simulate and integrate, and because it is simple and straightforward, Monte Carlo is easy to use. The Monte Carlo BEAMnrc code is one of the most common diagnostic X-ray simulation codes used in this study. Method: In one of the understudy hospitals, a certain number of CT scan images of patients who had previously been imaged were extracted from the hospital database. BEAMnrc software was used for simulation. The simulation of the head of the device with the energy of 0.09 MeV with 500 million particles was performed, and the output data obtained from the simulation was applied for phantom construction using CT CREATE software. The percentage of depth dose (PDD) was calculated using STATE DOSE was then compared with international standard values. Results and Discussion: The ratio of surface dose to depth dose (D/Ds) in the measured energy was estimated to be about 4% to 8% for bone and 3% to 7% for bone marrow. Conclusion: MC simulation is an efficient and accurate method for simulating bone marrow and calculating the absorbed dose.

Keywords: Monte Carlo, absorption dose, BEAMnrc, bone marrow

Procedia PDF Downloads 207

Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

Abstract:

Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

Procedia PDF Downloads 141

Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

Abstract:

An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

Procedia PDF Downloads 439

Authors: Assem M. F. Sallam, Ah. El-S. Makled

Abstract:

This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

Procedia PDF Downloads 270

Authors: Htay Htay Yi, Zin May Aye

Abstract:

Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

Procedia PDF Downloads 114

Authors: Neda Azari Dodaran, Hamid Ahmadi

Abstract:

Results of 405 finite element (FE) analyses were used in the present research to study the effect of the joint geometry on the ultimate strength and initial stiffness of tubular K-joints subjected to axial loading at fire-induced elevated temperatures. The FE models were validated against the data available from experimental tests. Structural behavior under different temperatures (200ºC, 400ºC, 500ºC, and 700ºC) was investigated and compared to the behavior at ambient temperature (20ºC). A parametric study was conducted to investigate the effect of dimensionless geometrical parameters (β, γ, θ, and τ) on the ultimate strength and initial stiffness. Afterwards, ultimate strength data extracted from the FE analyses were compared with the values calculated from the equations proposed by available design codes in which the ultimate strength of the joint at elevated temperatures is obtained by replacing the yield stress of the steel at ambient temperature with the corresponding value at elevated temperature. It was indicated that this method may not have acceptable accuracy for K-joints under axial loading. Hence, a design formula was developed, through nonlinear regression analyses, to determine the ultimate strength of K-joints subjected to balanced axial loads at elevated temperatures.

Keywords: axial loading, elevated temperature, parametric equation, static strength, tubular K-joint

Procedia PDF Downloads 144

Authors: Mohamed I. Mahrous, Mohamed G. Ashmawy

Abstract:

Hybrid genetic algorithm (HGA) is proposed in this paper to determine the economic scheduling of electric power generation over a fixed time period under various system and operational constraints. The proposed technique can outperform conventional genetic algorithms (CGAs) in the sense that HGA make it possible to improve both the quality of the solution and reduce the computing expenses. In contrast, any carefully designed GA is only able to balance the exploration and the exploitation of the search effort, which means that an increase in the accuracy of a solution can only occure at the sacrifice of convergent speed, and vice visa. It is unlikely that both of them can be improved simultaneously. The proposed hybrid scheme is developed in such a way that a simple GA is acting as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method (pattern search technique) is next employed to do the fine tuning. The aim of the strategy is to achieve the cost reduction within a reasonable computing time. The effectiveness of the proposed hybrid technique is verified on two real public electricity supply systems with 13 and 40 generator units respectively. The simulation results obtained with the HGA for the two real systems are very encouraging with regard to the computational expenses and the cost reduction of power generation.

Keywords: genetic algorithms, economic dispatch, pattern search

Procedia PDF Downloads 434

Authors: Zabeehullah, Fahim Arif, Yawar Abbas

Abstract:

Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

Procedia PDF Downloads 106

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

Procedia PDF Downloads 429

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

Abstract:

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

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

Procedia PDF Downloads 217

Authors: Amir Mahyar Khorasani, Ian Gibson, Moshe Goldberg, Mohammad Masoud Movahedi, Guy Littlefair

Abstract:

One of the important factors in manufacturing processes especially machining operations is surface quality. Improving this parameter results in improving fatigue strength, corrosion resistance, creep life and surface friction. The reliability and clearance of removable joints such as thread and nuts are highly related to the surface roughness. In this work, the effect of different cutting parameters such as cutting fluid pressure, feed rate and cutting speed on the surface quality of the crest of thread in the high-speed milling of Brass C3600 have been determined. Two popular neural networks containing MLP and RBF coupling with Taguchi L32 have been used to model surface roughness which was shown to be highly adept for such tasks. The contribution of this work is modelling surface roughness on the crest of the thread by using precise profilometer with nanoscale resolution. Experimental tests have been carried out for validation and approved suitable accuracy of the proposed model. Also analysing the interaction of parameters two by two showed that the most effective cutting parameter on the surface value is feed rate followed by cutting speed and cutting fluid pressure.

Keywords: artificial neural networks, cutting conditions, high-speed machining, surface roughness, thread milling

Procedia PDF Downloads 370

Authors: M. Kessi

Abstract:

We investigated the effect of the magnetic field on carrier transport phenomena in the transistor channel region of Double-Gate Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET). This explores the Lorentz force and basic physical properties of solids exposed to a constant external magnetic field. The magnetic field modulates the electrons and potential distribution in the case of silicon Tunnel FETs. This modulation shows up in the device's external electrical characteristics such as ON current (ION), subthreshold leakage current (IOF), the threshold voltage (VTH), the magneto-transconductance (gm) and the output magneto-conductance (gDS) of Tunnel FET. Moreover, the channel doping concentration and potential distribution are obtained using the numerical method by solving Poisson’s transport equation in 3D modules semiconductor magnetic sensors available in Silvaco TCAD tools. The numerical simulations of the magnetic nano-sensors are relatively new. In this work, we present the results of numerical simulations based on 3D magnetic sensors. The results show excellent accuracy comportment and good agreement compared with that obtained in the experimental study of MOSFETs technology.

Keywords: single-gate MOSFET, magnetic field, hall field, Lorentz force

Procedia PDF Downloads 176

Authors: Davood Barari Tari

Abstract:

In order to investigate the correlation of rice traits in different nitrogen management methods by modeling programming, an experiment was laid out in rice paddy field in an experimental field at Caspian Coastal Sea region from 2013 to 2014. Variety used was Shiroudi as a high yielding variety. Nitrogen management was in two methods. Amount of nitrogen at four levels (30, 60, 90, and 120 Kg N ha-1 and control) and nitrogen-splitting at four levels (T1: 50% in base + 50% in maximum tillering stage, T2= 33.33% basal +33.33% in maximum tillering stage +33.33% in panicle initiation stage, T3=25% basal+37.5% in maximum tillering stage +37.5% in panicle initiation stage, T4: 25% in basal + 25% in maximum tillering stage + 50% in panicle initiation stage). Results showed that nitrogen traits, total grain number, filled spikelets, panicle number per m2 had a significant correlation with grain yield. Results related to calibrated and validation of rice model methods indicated that correlation between rice yield and yield components was accurate. The correlation between panicle length and grain yield was minimum. Physiological indices was simulated with low accuracy. According to results, investigation of the correlation between rice traits in physiological, morphological and phenological characters and yield by modeling and simulation methods are very useful.

Keywords: rice, physiology, modelling, simulation, yield traits

Procedia PDF Downloads 338

Authors: Abdelrahman Mohamed Abdelrahman

Abstract:

Canopic jars are one of the vessels of funerary nature used by the ancient Egyptian in mummification process that were used to save the viscera of the mummified body after being extracted from the body and treated. Canopic jars are made of several types of materials like Limestone, Alabaster, and Pottery. The studied canopic jar dates back to Late period, located in the Grand Egyptian Museum (GEM), Giza, Egypt. This jar carved from limestone with carved hieroglyphic inscriptions, and it filled and closed by mortar from inside. Some aspects of damage appeared in the jar, such as dust, dirts, classification, wide crack, weakness of limestone. In this study, we used documentation and investigation modern techniques to document and examine the jar. 3D scanning and X-ray Radiography imaging used in applied study. X-ray imaging showed that the mortar was placed at a time when the jar contained probably viscera where the mortar appeared that not reach up to the base of the inner jar. Through the three-dimensional photography, the jar was documented, and we have 3D model of the jar, and now we have the ability through the computer to see any part of the jar in all its details. After that, conservation procedures have been applied with high accuracy to conserve the jar, including mechanical, wet, and chemical cleaning, filling wide crack in the body of the jar using mortar consisting of calcium carbonate powder mixing with primal E330 S, and consolidation, so the limestone became strong after using paraloid B72 2% concentrate as a consolidate material.

Keywords: vessel, limestone, canopic jar, mortar, 3D scanning, X-ray radiography

Procedia PDF Downloads 67

Authors: Hossein Alimohammadi, Mohsen Amirmojahedi, Mehrdad Rowhani

Abstract:

Soil properties are used by geotechnical engineers to evaluate and analyze site conditions for designing purposes. Although basic soil classification tests are easy to perform and provide useful information to determine the properties of soils, it may take time to get the result and add some costs to the projects. Standard Penetration Test (SPT) provides an opportunity to evaluate soil parameters without performing laboratory tests. In addition to its simplicity and cheapness, the results become available immediately. This research provides a guideline on the application of the SPT test method, reliability of adapting the SPT test results in evaluating soil physical and mechanical properties such as Atterberg limits, shear strength, and compressive strength compressibility parameters. A total of 70 boreholes were investigated in this study by taking soil samples between depths of 1.2 to 15.25 meters. The project site was located in Morrow County, Ohio. A regression-based formula was proposed based on Tobit regression with a stepwise variable selection analysis conducted between SPT and other typical soil properties obtained from soil tests. The results of the research illustrated that the shear strength and physical properties of the soil affect the SPT number. The proposed correlation can help engineers to use SPT test results in their design with higher accuracy.

Keywords: standard penetration test, soil properties, soil classification, regression method

Procedia PDF Downloads 183

Authors: Collen Tebogo Masilo, Erik Schmikl

Abstract:

The demand for the DataMiner product by customers has presented a great challenge for the vendor in Skyline Communications in deploying its limited resources in the form of human resources, financial resources, and office space, to achieve high organisational performance in all its international operations. The rapid growth of the organisation has been unable to efficiently support its existing customers across the globe, and provide services to new customers, due to the limited number of approximately one hundred employees in its employ. The combined descriptive and explanatory case study research methods were selected as research design, making use of a survey questionnaire which was distributed to a sample of 100 respondents. A sample return of 89 respondents was achieved. The sampling method employed was non-probability sampling, using the convenient sampling method. Frequency analysis and correlation between the subscales (the four themes) were used for statistical analysis to interpret the data. The investigation was conducted into mechanisms that can be deployed to balance the high demand for products and the limited production capacity of the company’s Belgian operations across four aspects: demand management strategies, capacity management strategies, communication methods that can be used to align a sales management department, and reward systems in use to improve employee performance. The conclusions derived from the theme ‘demand management strategies’ are that the company is fully aware of the future market demand for its products. However, there seems to be no evidence that there is proper demand forecasting conducted within the organisation. The conclusions derived from the theme 'capacity management strategies' are that employees always have a lot of work to complete during office hours, and, also, employees seem to need help from colleagues with urgent tasks. This indicates that employees often work on unplanned tasks and multiple projects. Conclusions derived from the theme 'communication methods used to align sales management department with operations' are that communication is not good throughout the organisation. This means that information often stays with management, and does not reach non-management employees. This also means that there is a lack of smooth synergy as expected and a lack of good communication between the sales department and the projects office. This has a direct impact on the delivery of projects to customers by the operations department. The conclusions derived from the theme ‘employee reward systems’ are that employees are motivated, and feel that they add value in their current functions. There are currently no measures in place to identify unhappy employees, and there are also no proper reward systems in place which are linked to a performance management system. The research has made a contribution to the body of research by exploring the impact of the four sub-variables and their interaction on the challenges of organisational productivity, in particular where an organisation experiences a capacity problem during its growth stage during tough economic conditions. Recommendations were made which, if implemented by management, could further enhance the organisation’s sustained competitive operations.

Keywords: high demand for products, high organisational performance, limited production capacity, limited resources

Procedia PDF Downloads 139

Authors: Retno A. S. Lestari, Wahyudi B. Sediawan, Siti Syamsiah, Sarto

Abstract:

Sulfur-oxidizing bacteria were isolated and then grown on salak fruit seeds forming a biofilm on the surface. Their performances in sulfide removal were experimentally observed. In doing so, the salak fruit seeds containing biofilm were then used as packing material in a cylinder. Biogas obtained from biological treatment, which contains 27.95 ppm of hydrogen sulfide was flown through the packed bed. The hydrogen sulfide from the biogas was absorbed in the biofilm and then degraded by the microbes in the biofilm. The hydrogen sulfide concentrations at a various axial position and various times were analyzed. A set of simple kinetics model for the rate of the sulfide removal and the bacterial growth was proposed. Since the biofilm is very thin, the sulfide concentration in the Biofilm at a certain axial position is assumed to be uniform. The simultaneous ordinary differential equations obtained were then solved numerically using Runge-Kutta method. The values of the parameters were also obtained by curve-fitting. The accuracy of the model proposed was tested by comparing the calculation results using the model with the experimental data obtained. It turned out that the model proposed can describe the removal of sulfide liquid using bio-filter in the packed bed. The biofilter could remove 89,83 % of the hydrogen sulfide in the feed at 2.5 hr of operation and biogas flow rate of 30 L/hr.

Keywords: sulfur-oxidizing bacteria, salak fruit seeds, biofilm, packing material, biogas

Procedia PDF Downloads 211

Authors: Sheriff Muhammad Ibrahim, Tijjani Muhammad

Abstract:

The study assesses the Islamic Microfinance Bank's role in promoting customers' social welfare, using the newly developed products of Yobe Microfinance Bank to encourage inclusion and alleviate poverty in the Yobe communities. Yobe state is ranked bottom as the poorest in the region and scores low on human development and poverty alleviation. It is clearly indicated low education rates, poor implementation of government policies on poverty, and a high rate of financial exclusion. The study adopted a qualitative approach using random sampling to collect data from customers of Yobe Microfinance Bank. Using the acceptability of the newly introduced sharia complaint products of Yobe Microfinance among the people in Yobe state, using the Structural Equation Modelling, a total of 300 respondents completed the survey using a Likert scale. The study employed Structural Equation Modeling to analyze and test reliability and validity to provide accuracy of respondents' information. The finding indicates the positive relationship between Islamic banking products and customer satisfaction. The study concludes that introducing and consistently managing Islamic products can improve social welfare and reduce poverty through financial inclusion in the state.

Keywords: islamic microfinance, social welfare, products, poverty

Procedia PDF Downloads 120

Authors: Hassan. A. Abas, Saad A. Aiban

Abstract:

Soil improvement by means of stone column method is used to improve sabkha soils in order to limit total and differential settlement and to achieve the required bearing capacity. Full-scale plate test was performed on site to confirm the achievement of required bearing capacity at the specified settlement. Despite the fact that this technique is widely used to improve sabkha soils, there are no studies focusing on the behavior of stone columns in such problematic soils. Sabkha soils are known for its high compressibility, low strength and water sensitivity due to loss of salt cementation upon flooding during installation of stone columns. Numerical modeling of plate load test assist to understand complicated behavior of sabkha – stone column interaction. This paper presents a three-dimensional Finite element model, using PLAXIS 3D software, to simulate vertical plate load tests on a stone column installed in sabkha. The predicted settlement values are in reasonable agreement with the field measure values and the field load - settlement curve can be predicted with good accuracy.

Keywords: soil improvement, stone column, sabkha, PLAXIS 3D

Procedia PDF Downloads 382

Authors: Ruchi Makani, B. V. R. Reddy

Abstract:

Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

Procedia PDF Downloads 168

Authors: Saeed Kamarian

Abstract:

In this paper, free vibrations of Functionally Graded Sandwich (FGS) beams reinforced by randomly oriented Single-Walled Carbon Nanotubes (SWCNTs) are investigated. The Eshelby–Mori–Tanaka approach based on an equivalent fiber is used to investigate the material properties of the structure. The natural frequencies of the FGS nanocomposite beam are analyzed based on various Higher-order Shear Deformation Beam Theories (HSDBTs) and using an analytical method. The verification study represents the simplicity and accuracy of the method for free vibration analysis of nanocomposite beams. The effects of carbon nanotube volume fraction profiles in the face layers, length to span ratio and thicknesses of face layers on the natural frequency of structure are studied for the different HSDBTs. Results show that by utilizing the FGS type of structures, free vibration characteristics of structures can be improved. A comparison is also provided to show the difference between natural frequency responses of the FGS nanocomposite beam reinforced by aligned and randomly oriented SWCNT.

Keywords: sandwich beam, nanocomposite beam, functionally graded materials, higher-order beam theories, Mori-Tanaka approach

Procedia PDF Downloads 455

Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

Procedia PDF Downloads 145

Authors: Karissa A. Graham

Abstract:

Pyoderma gangrenosum (PG) is a prototypic autoinflammatory neutrophilic dermatosis that is a rare disorder. It presents a diagnostic challenge owing to its variable presentation, clinical overlap with other conditions, it is often associated with other systemic conditions, and there is no definitive histological or laboratory characteristic. The Delphai consensus for PG includes the presence of at least one ulcer on the anterior lower limb. Systemic corticosteroids and immunosuppressive therapies are the mainstay treatment for PG. We describe a case report of delayed diagnosis of ulcerative pyoderma gangrenosum in a 44-year-old male on his forearm. The patient presented with an infected ulcer on his right forearm that had been present for over three years. The patient was a Type 2 Diabetic with no personal or family history of inflammatory bowel disease or other autoimmune diseases. The patient was initially investigated for malignancy, but biopsies returned as chronic inflammatory tissue with neutrophilic infiltrate and no malignancy. The patient was commenced on systemic prednisone for the treatment of pyoderma gangrenosum. The diagnosis of ulcerative PG poses a challenge given the vast differential diagnosis for a cutaneous ulcer (i.e., malignant, vascular, autoimmune, trauma, infective, etc.). Diagnostic accuracy is important given that the treatment for PG with steroids does not go without risks and indeed may be contraindicated in other potential causes of the ulcer. Indeed, more common and more sinister causes of ulcers should be investigated first, as death from PG is quite rare.

Keywords: dermatological diagnosis, dermatosis, pyoderma gangrenosum, rare presentation

Procedia PDF Downloads 87

Authors: Tatiana G. Smirnova, Stan G. Benjamin

Abstract:

Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

Procedia PDF Downloads 80

Authors: A. Selmi

Abstract:

Free vibration analysis of homogenous and axially functionally graded simply supported beams within the context of Euler-Bernoulli beam theory is presented in this paper. The material properties of the beams are assumed to obey the linear law distribution. The effective elastic modulus of the composite was predicted by using the rule of mixture. Here, the complexities which appear in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using a relatively new approach called the Differential Transformation Method. This technique is applied for solving differential equation of transverse vibration of axially functionally graded beams. Natural frequencies and corresponding normalized mode shapes are calculated for different Young’s modulus ratios. MATLAB code is designed to solve the transformed differential equation of the beam. Comparison of the present results with the exact solutions proves the effectiveness, the accuracy, the simplicity, and computational stability of the differential transformation method. The effect of the Young’s modulus ratio on the normalized natural frequencies and mode shapes is found to be very important.

Keywords: differential transformation method, functionally graded material, mode shape, natural frequency

Procedia PDF Downloads 298

Authors: Yi Zheng

Abstract:

Improving formability and mechanical properties have always been one of the challenges in the field of additive manufacturing (AM) of nickel-based superalloys. In this work, the effect of a coaxially coupled alternating magnetic field (AMF) on surface morphology and mechanical properties of plasma arc-based additive manufactured Inconel 718 deposit were investigated. Results show that the Lorentz force induced by AMF strongly alters the flow behavior of the plasma jet and the molten pool, suppressing the tendency of the liquid metal in the molten pool to flow down on the two sides face of the deposit, which in turn remarkably improved the surface accuracy of the thin-walled deposit. Furthermore, the electromagnetic stirring induced by AMF can effectively enhance the convection between the dendrites, which could not only contribute to the formation of finer dendrites but also alleviate the enrichment of the elements (i.e., Nb and Mo) at the solid-liquid interface and inhibits the precipitation of Laves phase. The smallest primary dendritic arm spacing (~13 μm) and lowest Laves phases area fraction (3.12%) were witnessed in the bottom region of the AMF-assisted deposit. The mechanical test confirmed that the deposit's micro-hardness and tensile properties were moderately improved compared with the counterpart without AMF.

Keywords: additive manufacturing, inconel 718, alternating magnetic field, laves phase

Procedia PDF Downloads 76

Authors: Sofiane Bououden, Ilyes Boulkaibet

Abstract:

In this paper, a robust fault-tolerant predictive control (FTPC) strategy is proposed for systems with linear parameter varying (LPV) models and input constraints subject to sensor faults. Generally, virtual observers are used for improving the observation precision and reduce the impacts of sensor faults and uncertainties in the system. However, this type of observer lacks certain system measurements which substantially reduce its accuracy. To deal with this issue, a real observer is then designed based on the virtual observer, and consequently a real observer-based robust predictive control is designed for polytopic LPV systems. Moreover, the proposed observer can entirely assure that all system states and sensor faults are estimated. As a result, and based on both observers, a robust fault-tolerant predictive control is then established via the Lyapunov method where sufficient conditions are proposed, for stability analysis and control purposes, in linear matrix inequalities (LMIs) form. Finally, simulation results are given to show the effectiveness of the proposed approach.

Keywords: linear parameter varying systems, fault-tolerant predictive control, observer-based control, sensor faults, input constraints, linear matrix inequalities

Procedia PDF Downloads 194

Authors: A. Saimen, E. Armstrong, C. Manitshana

Abstract:

Intimate partner violence (IPV) has been recognised as a global human rights violation. It is universally under diagnosed and the institution of timeous multi-faceted interventions has been noted to benefit IPV victims. Currently, the concept of using a screening tool to detect IPV has not been widely explored in a primary healthcare setting in South Africa, and it was for this reason that this study has been undertaken. A systematic random sampling of 1 in 8 women over a period of 3 months was conducted prospectively at the OPD of a Level 1 Hospital. Participants were asked about their experience of IPV during the past 12 months. The WAST-short, a two-question tool, was used to screen patients for IPV. To verify the result of the screening, women were also asked the remaining questions from the WAST. Data was collected from 400 participants, with a response rate of 99.3%. The prevalence of IPV in the sample was 32%. The WAST-short was shown to have the following operating characteristics: sensitivity 45.2%, specificity 98%,positive predictive value 98%, negative predictive value 79%. The WAST-short lacks sufficient sensitivity and therefore is not an ideal screening tool for this setting. Improvement in the sensitivity of the WAST-short in this setting may be achieved by lowering the threshold for a positive result for IPV screening, and modification of the screening questions to better reflect IPV as understood by the local population.

Keywords: domestic violence, intimate partner violence, screening, screening tools

Procedia PDF Downloads 301

Authors: Sukhvinder Kaur, Ashok Agarwal

Abstract:

Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

Procedia PDF Downloads 209

Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

Abstract:

The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

Procedia PDF Downloads 119