Search results for: bit error rate (BER)

Authors: Fereshteh Darash

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Reflective tax management corresponds to the Agency Theory since it determines the motivation of managers for tax management actions and short-term and long-term consequences. Therefore, selection of tax strategy contributes to the tax and financial position of the firm in the future. The aim of the present research is to evaluate the effect of tax management components on risk-taking of firms listed in Tehran stock exchange by using regression analysis method. Results show that tax effective rate, tax risk and tax planning have no significant effect on the firm's future risk. Results suggest that stakeholders assess the effective tax rate and delay in tax payment in line with their benefits. They tend to accept the higher risk cost for reduction of tax payments and benefits of higher liquidity in current period. Hence, effective tax rate and tax risk have no significant effect on future risk of the firm. Moreover, tax planning yields no information regarding the predictability of the future profits and as a result, it has no significant effect on the future risk of the firm since specific goals of financial reporting are in priority for the stakeholders and regardless of the firm’s data analysis, they take investment decisions and they less intend to purchase the stocks in a rational manner.

Keywords: tax management, tax effective rate, tax risk, tax planning, firm risk

Procedia PDF Downloads 137

Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

Procedia PDF Downloads 696

Authors: Peter U. Eze, P. Udaya, Robin J. Evans

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Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

Procedia PDF Downloads 197

Authors: H. Tanyildizi, M. Abuqebitah, I. Cavdar, M. Demir, L. Kabasakal

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Aim: Whole liver radiation has the modest benefit in the treatment of unresectable hepatic metastases but the radiation doses must keep in control. Otherwise, RILD complications may arise. In this study, we aimed to calculate amount of maximum permissible activity (MPA) and critical organ absorbed doses with MIRD methodology, to evaluate tumour doses for treatment response and whole liver doses for RILD and to find optimal liver function test additionally. Materials and Methods: This study includes 29 patients who attended our nuclear medicine department suffering from Y-90 microspheres treatment. 10 mCi Tc-99m MAA was applied to the patients for dosimetry via IV. After the injection, whole body SPECT/CT images were taken in one hour. The minimum therapeutic tumour dose is on the point of being 120 Gy1, the amount of activities were calculated with MIRD methodology considering volumetric tumour/liver rate. A sub-working group was created with 11 patients randomly and liver clearance rate with Tc-99m-Mebrofenin was calculated according to Ekman formalism. Results: The volumetric tumour/liver rates were found between 33-66% (Maksimum Tolarable Dose (MTD) 48-52Gy3) for 4 patients, were found less than 33% (MTD 72Gy3) for 25 patients. According to these results the average amount of activity, mean liver dose and mean tumour dose were found 1793.9±1.46 MBq, 32.86±0.19 Gy, and 138.26±0.40 Gy. RILD was not observed in any patient. In sub-working group, the relationship between Bilirubin, Albumin, INR (which show presence of liver disease and its degree), liver clearance with Tc-99m-Mebrofenin and calculated activity amounts were found r=0.49, r=0.27, r=0.43, r=0.57, respectively. Discussions: The minimum tumour dose was found 120 Gy for positive dose-response relation. If volumetric tumour/liver rate was > 66%, dose 30 Gy; if volumetric tumour/liver rate 33-66%, dose escalation 48 Gy; if volumetric tumour/liver rate < 33%, dose 72 Gy. These dose limitations did not create RILD. Clearance measurement with Mebrofenin was concluded that the best method to determine the liver function. Therefore, liver clearance rate with Tc-99m-Mebrofenin should be considered in calculation of yttrium-90 microspheres dosimetry.

Keywords: clearance, dosimetry, liver, RILD

Procedia PDF Downloads 440

Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: Ayad Dalloo, Sulaf Dalloo

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Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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Authors: Ram Dhani chauhan

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Tribology is a term that was developed from the Greek words ‘tribos’ (rubbing) and ‘logy’ (knowledge). In other words, a study of wear, friction and lubrication of material is known as Tribology. In groundwater irrigation, the life of submersible pump components like impeller, bush and wear ring will depend upon the wear and corrosion resistance of casted material. Leaded tin bronze (LTB) is an easily castable material with good mechanical properties and tribological behaviour and is utilised in submersible pumps at large. It has been investigated that, as Sn content increases from 4-8 wt. % in LTB alloys, the hardness of the alloys increases and the wear rate decreases. Similarly, a composite of copper with 3% wt. Graphite (threshold limit of mix) has a lower COF (coefficient of friction) and the lowest wear rate. In LTB alloys, in the initial low-speed range, wear increases and in the higher range, it was found that wear rate decreases.

Keywords: coefficent of friction, coefficient of wear, tribology, leaded tin bronze

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Authors: Ijaz Ahmad

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Weed competition is one of the major biotic constraints in wheat crop productivity. Avena fatua L. and Silybum marianum (L.) Gaertn. are among the worst weeds of wheat, greatly deteriorating wheat quality subsequently reducing its market value. In this connection, two-year experiments were conducted in 2018 & 2019. Different seeding rate wheat viz; 80, 100, 120 and 140 kg ha-1 and different weeds ratio (A. fatua: S. marianum ) sown at the rate 1:8, 2:7, 3:6, 4:5, 5:4, 6:3, 7:2, 8:1 and 0:0 respectively. The weeds ratio and wheat densities are indirectly proportional. However, the wheat seed at the rate of 140 kg ha-1 has minimal weeds interference. Yield losses were 17.5% at weeds density 1:8 while 7.2% at 8:1. However, in wheat density, the highest percent losses were computed on 80 kg ha-1 while the lowest was recorded on 140 kg ha-1. Since due to the large leaf canopy of S. marianum other species can't sustain their growth. Hence, it has been concluded that S. marianum is the hotspot that causes reduction to the yield-related parameters, followed by A. fatua and the other weeds. Due to the morphological mimicry of A. fatua with wheat crop during the vegetative growth stage, it cannot be easily distinguished. Therefore, managing A. fatua and S. marianum before seed setting is recommended for reducing the future weed problem. Based on current studies, it is suggested that sowing wheat seed at the rate of 140 kg ha-1 is recommended to better compete with all the field weeds.

Keywords: fat content, holly thistle, protein content, weed competition, wheat, wild oat

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Authors: Le-Quyen Nguyen, Hoang Van Bui, Ngoc Thi Tran, Binh Thanh Le, Linus Olson, Thanh Quang Le

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Objective: We compared of outcomes between infected and non-infected COVID-19 pregnant at the largest obstetrics and gynecology hospital in southern Vietnam. Materials and Methods: A retrospective study was conducted at gestational age (GA) 28-42 weeks, who terminated pregnancy and had a real-time PCR test for SARS-CoV-2 at Tu Du Hospital. Demographic, clinical, laboratory, and epidemiological data were collected from hospital electronic-medical-records. Diagnosis and screening of SARS-CoV-2 used Real-time-PCR. Results: From July to October 2021, 9,246 pregnant with GA of 28-42 weeks were delivered, including 664 infected with COVID-19 and 8,582 non-infected. The cesarean section (CS) rates of pregnant with and without COVID-19 were 47.3% and 46.0%. At GA 32-34 weeks, the rate of CS with COVID-19 was 5.07 times higher than without. The rate of postpartum hemorrhage (PPH) and the Apgar score between these two groups were similar. The mortality rate of infected pregnants was 2.26%. Conclusions: COVID-19 infection increased the CS rate in the group of preterm pregnancies from 32 to less than 34 weeks. COVID-19 did not increase the risk of complications related to adverse pregnancy outcomes such as PPH, Apgar scores, the ratio of stillbirths, deaths due to malformation, and fetal deaths in labor.

Keywords: COVID-19, SARS-CoV-2, pregnancy, outcome, vietnam

Procedia PDF Downloads 138

Authors: Medhin Haftom Hailu

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The advancement of information technology has significantly impacted Ethiopia's economy, driving innovation, productivity, job creation, and global connectivity. This research examined the impact of contemporary information and communication technologies on Ethiopian economic progress. The study examined eight variables, including mobile, internet, and fixed-line penetration rates, and five macroeconomic control variables. The results showed a positive and strong effect of ICT on economic growth in Ethiopia, with 1% increase in mobile, internet, and fixed line services penetration indexes resulting in an 8.03, 10.05, and 30.06% increase in real GDP. The Granger causality test showed that all ICT variables Granger caused economic growth, but economic growth Granger caused mobile penetration rate only. The study suggests that coordinated ICT infrastructure development, increased telecom service accessibility, and increased competition in the telecom market are crucial for Ethiopia's economic growth. Ethiopia is attempting to establish a digital economy through massive investment in ensuring ICT quality and accessibility. Thus, the research could enhance in understanding of the economic impact of ICT expansion for successful ICT policy interventions for future research.

Keywords: economic growth, cointegration and error correction, ICT expansion, granger causality, penetration

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Authors: Jayeola Olabisi, T. Olawale Oladunjoye, Ademola A. Adewumi

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The study empirically examines the relationship that exists between the economic environment and entrepreneurial development in Nigeria. A structured questionnaire is administered on the study and data collected are analysed using Analysis of Variance and Regression. The following variables are indices of determination; Interest Rate (IR); Income Tax (IT). The results of the study show that there is a significant relationship between IR and ED in Nigeria (p < 0.5) with a positive correlation (r=0.526, r2=0.276). Also, there is a significant relationship between IT and ED in Nigeria (p < 0.05), with a positive association (r=0.546; r2=0.299). The study concludes that the emergence of the higher level of the stable economic environment is critical to entrepreneurial development in Nigeria. Therefore, government involvement in public private partnership for infrastructural development, enlargement of productive, judicious and transparent use of funds collected from income tax and affordable interest rate will galvanise the inward sourcing of raw materials that boost entrepreneurial development in Nigeria.

Keywords: interest rate, income tax, business environment and entrepreneurial development

Procedia PDF Downloads 363

Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

Procedia PDF Downloads 242

Authors: Nagasamy Venkatesh Dhandapani, Amged Awad El-Gied

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Cefixime, a BCS class II drug, is insoluble in water but freely soluble in acetone and in alcohol. The aqueous solubility of cefixime in water is poor and exhibits exceptionally slow and intrinsic dissolution rate. In the present study, cefixime and β-Cyclodextrin (β-CD) solid dispersions were prepared with a view to study the effect and influence of β-CD on the solubility and dissolution rate of this poorly aqueous soluble drug. Phase solubility profile revealed that the solubility of cefixime was increased in the presence of β-CD and was classified as A_L-type. Effect of variable, such as drug:carrier ratio, was studied. Physical characterization of the solid dispersion was characterized by Fourier transform infrared spectroscopy (FT-IR) and Differential scanning calorimetry (DSC). These studies revealed that a distinct loss of drug crystallinity in the solid molecular dispersions is ostensibly accounting for enhancement of dissolution rate in distilled water. The drug release from the prepared solid dispersion exhibited a first order kinetics. Solid dispersions of cefixime showed a 6.77 times fold increase in dissolution rate over the pure drug.

Keywords: β-cyclodextrin, cefixime, dissolution, Kneading method, solid dispersions, release kinetics

Procedia PDF Downloads 316

Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

Procedia PDF Downloads 578

Authors: Mohamed Hamza, Alex Ohoussou

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At JAWDA, our primary focus is on ensuring the satisfaction of our clients worldwide. We are committed to delivering new features on our SaaS platform as quickly as possible while maintaining high-quality standards. In this paper, we highlight two key aspects of testing that represent an evolution of current methods and a potential trend for the future, which have enabled us to uphold our commitment effectively. These aspects are: "One Sandbox per Pull Request" (dynamic test environments instead of static ones) and "QA for All.".

Keywords: QA for all, dynamic sandboxes, QAOPS, CICD, continuous testing, all testers, QA matters for all, 1 sandbox per PR, utilization rate, coverage rate

Procedia PDF Downloads 34

Authors: Ahsan Ullah

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The aim of this study is to measure the relationship between sedentary behaviour and metabolic rate among adult professionals. An intervention (e-mobile) approach was used for gathered the information from the participants. A total of 40 participants (men = 30, and women = 10) with an average age of (36.53 years ± 8.85) were randomly assigned to an intervention group (n= 20) and control group (n= 20). All the participants completed the Sedentary Behaviour Questionnaire (SBQ) and The International Physical Activity Questionnaire (IPAQ) at baseline and at the end of eight weeks. The participants in the intervention group were given physical activity guidelines targeted at increasing physical activity levels during daily activities. On the other side, the control group was advised to continue with their routine daily physical activity. Statistical analyses, including descriptive statistics and inferential analysis like mean, SD, T-tests, and ANOVA, were used to analyze the data and determine relationships between variables. After analyzing the data, the results showed that significant difference in pre and post metabolic rate scores (1488.31 ± 179.13 to 1468.44 ± 128.19) (f = 10.83, p < 0.000) were noted in the experimental group after eight week. The experimental group increased their walking (863.78 METs per week to 1625.55 METs per week), moderate activity (295 METs per week to 743 METs per week) and vigorous activity (362 METs per week to 1366 METs per week) physical activity (all p<0.001). There were no significant differences observed in any outcome measured before and after eight weeks in the control group. These findings suggest that engaging in physical activity can effectively improve metabolic rate and reduce sedentary behavior among physically active adults.

Keywords: sedentary behavior, metabolic rate, adult’s professionals, physical activity

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Authors: Ehsan Mehryaar

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The rate of penetration is (RoP) one of the vital factors in the cost and time of tunnel boring projects; therefore, predicting it can lead to a substantial increase in the efficiency of the project. RoP is heavily dependent geological properties of the project site and TBM properties. In this study, 151-point data from Queen’s water tunnel is collected, which includes unconfined compression strength, peak slope index, angle with weak planes, and distance between planes of weaknesses. Since the size of the data is small, it was observed that it is imbalanced. To solve that problem synthetic minority oversampling technique is utilized. The model based on the model tree is proposed, where each leaf consists of a support vector machine model. Proposed model performance is then compared to existing empirical equations in the literature.

Keywords: Model tree, SMOTE, rate of penetration, TBM(tunnel boring machine), SVM

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Authors: Dojoon Jung, Kiwoong Moon, Joong Lee

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The height of criminals is one of the important clues that can determine the scope of the suspect's search or exclude the suspect from the search target. Although measuring the height of criminals by video alone is limited by various reasons, the 3D data of the scene and the Closed Circuit Television (CCTV) footage are matched, the height of the criminal can be measured. However, it is still difficult to measure the height of CCTV footage in the non-contact type measurement method because of variables such as position, posture, and head shape of criminals. In this paper, we propose a method of matching the CCTV footage with the 3D data on the crime scene and measuring the height of the person using the 3D human body model in the matched data. In the proposed method, the height is measured by using 3D human model in various scenes of the person in the CCTV footage, and the measurement value of the target person is corrected by the measurement error of the replay CCTV footage of the reference person. We tested for 20 people's walking CCTV footage captured from an indoor and an outdoor and corrected the measurement values with 5 reference persons. Experimental results show that the measurement error (true value-measured value) average is 0.45 cm, and this method is effective for the measurement of the person's height in CCTV footage.

Keywords: human height, CCTV footage, 2D/3D matching, 3D human body model

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Authors: Rajesh Kumar, Prabha Chand

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Fins and twisted tape inserts are widely used passive elements to enhance heat transfer rate in various engineering applications. The present paper describes the theoretical analysis of solar air heater fitted with fins and twisted tape inserts. Mathematical model is develop for this novel design of solar air heater and a MATLAB code is generated for the solution of the model. The effect of twist ratio, mass flow rate and inlet temperature on the thermal efficiency and exit air temperature has been investigated. The results are compared with the results of plane solar air heater. Results show a substantial enhancement in heat transfer rate, efficiency and exit air temperature.

Keywords: solar air heater, thermal efficiency, twisted tape, twist ratio

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Authors: Moayyad Shawaqfah, Ibtehal Alqdah, Amjad Adaileh

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Coridoor area (400 km2) lies to the north – east of Amman (60 km). It lies between 285-305 E longitude and 165-185 N latitude (according to Palestine Grid). It been subjected to exploitation of groundwater from new eleven wells since the 1999 with a total discharge of 11 MCM in addition to the previous discharge rate from the well field 14.7 MCM. Consequently, the aquifer balance is disturbed and a major decline in water level. Therefore, suitable groundwater resources management is required to overcome the problems of over pumping and its effect on groundwater quality. Three–dimensional groundwater flow model Processing Modeflow for Windows Pro (PMWIN PRO, 2003) has been used in order to calculate the groundwater budget, aquifer characteristics, and to predict the aquifer response under different stresses for the next 20 years (2035). The model was calibrated for steady state conditions by trial and error calibration. The calibration was performed by matching observed and calculated initial heads for year 2001. Drawdown data for period 2001-2010 were used to calibrate transient model by matching calculated with observed one, after that, the transient model was validated by using the drawdown data for the period 2011-2014. The hydraulic conductivities of the Basalt- A7/B2 aquifer System are ranging between 1.0 and 8.0 m/day. The low conductivity value was found at the north-west and south-western parts of the study area, the high conductivity value was found at north-western corner of the study area and the average storage coefficient is about 0.025. The water balance for the Basalt and B2/A7 formation at steady state condition with a discrepancy of 0.003%. The major inflows come from Jebal Al Arab through the basalt and through the limestone aquifer (B2/A7 12.28 MCMY aquifer and from excess rainfall is about 0.68 MCM/a. While the major outflows from the Basalt-B2/A7 aquifer system are toward Azraq basin with about 5.03 MCMY and leakage to A1/6 aquitard with 7.89 MCMY. Four scenarios have been performed to predict aquifer system responses under different conditions. Scenario no.2 was found to be the best one which indicates that the reduction the abstraction rates by 50% of current withdrawal rate (25.08 MCMY) to 12.54 MCMY. The maximum drawdowns were decreased to reach about, 7.67 and 8.38m in the years 2025 and 2035 respectively.

Keywords: Amman/Zarqa Basin, Jordan, groundwater management, groundwater modeling, modflow

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Authors: Milad Yousefi, Moslem Yousefi, Ricarpo Poley, Amer Nordin Darus

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Design optimization of heat exchangers is a very complicated task that has been traditionally carried out based on a trial-and-error procedure. To overcome the difficulties of the conventional design approaches especially when a large number of variables, constraints and objectives are involved, a new method based on a well-stablished evolutionary algorithm, particle swarm optimization (PSO), weighted sum approach and a novel constraint handling strategy is presented in this study. Since, the conventional constraint handling strategies are not effective and easy-to-implement in multi-objective algorithms, a novel feasibility-based ranking strategy is introduced which is both extremely user-friendly and effective. A case study from industry has been investigated to illustrate the performance of the presented approach. The results show that the proposed algorithm can find the near pareto-optimal with higher accuracy when it is compared to conventional non-dominated sorting genetic algorithm II (NSGA-II). Moreover, the difficulties of a trial-and-error process for setting the penalty parameters is solved in this algorithm.

Keywords: Heat exchanger, Multi-objective optimization, Particle swarm optimization, NSGA-II Constraints handling.

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Authors: Pushpendra S. Bharti, S. Maheshwari

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Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: electric discharge machining, material removal rate, surface roughness, too wear rate, multi-response signal-to-noise ratio, multi response signal-to-noise ratio, optimization

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Authors: Sudhanshu Kumar

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Electrical discharge machining, also known as EDM, process is one of the most applicable machining process for removal of material in hard to machine materials like superalloy metals. EDM process utilizes electrical energy into sparks to erode the metals in presence of dielectric medium. In the present investigation, superalloy, Inconel 718 has been selected as workpiece and electrolytic copper as tool electrode. Attempt has been made to understand the effect of size of tool with varying cavity depth during drilling of hole through EDM process. In order to systematic investigate, tool size in terms of tool diameter and cavity depth along with other important electrical parameters namely, peak current, pulse-on time and servo voltage have been varied at three different values and the experiments has been designed using fractional factorial (Taguchi) method. Each experiment has been repeated twice under the same condition in order to understand the variability within the experiments. The effect of variations in parameters has been evaluated in terms of material removal rate, tool wear rate and surface roughness. Results revel that change in tool diameter during machining affects the response characteristics significantly. Larger tool diameter yielded 13% more material removal rate than smaller tool diameter. Analysis of the effect of variation in cavity depth is notable. There is no significant effect of cavity depth on material removal rate, tool wear rate and surface quality. This indicates that number of experiments can be performed to analyze other parameters effect even at smaller depth of cavity which can reduce the cost and time of experiments. Further, statistical analysis has been carried out to identify the interaction effect between parameters.

Keywords: EDM, Inconel 718, material removal rate, roughness, tool wear, tool size

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Authors: Yubo Bi, Xiao Chen, Shouxiang Lu

Abstract:

A kind of gas-fueled burner, named Burning Rate Emulator, was proposed for the purpose of the emulation of condensed fuel recently. The gaseous fuel can be pure combustible fuel gas or blends of gaseous fuel or inert gas. However, this concept was recently proposed without detailed study on the combustion characteristic of fuel blends. In this study, two kinds of common gaseous fuels were selected, propane and acetylene, to provide the combustion heat as well as a large amount of smoke, which widely exists in liquid and solid fuel burning process. A set of experiments were carried out using a gas-fueled burner with a diameter of 8 cm. The total volume flow rate of propane and acetylene was kept at 3 liters per minute. The volume fraction of propane varied from 0% to 100% at interval of 10%. It is found that the flame height increases with propane volume fraction, which may be caused by the increase of heat release rate, as the energy density of propane is larger than that of acetylene. The dimensionless flame height is correlated against dimensionless heat release rate, which shows a power function relationship. The radiation fraction of the flame does not show a monotonic relationship with propane volume fraction. With the increase of propane volume fraction from 0% to 100%, the value of radiation fraction increases first and reach a maximum value around 0.46 at a propane volume fraction of 10%, and then decreases continuously to a value of 0.25 at the propane volume fraction of 100%. The flame radiation is related to the soot in the flame. The trend of the radiation fraction reflects that there may be a synergistic effect of soot formation between propane and acetylene which can be guessed from the significantly high radiation fraction at a propane volume fraction of 10%. This work provides data for combustion of gaseous fuel blends pool fire and also give reference on the design of Burning Rate Emulator.

Keywords: Burning Rate Emulator, fuel blends pool fire, flame height, radiation fraction

Procedia PDF Downloads 228

Authors: Auliya Adzillatin Uzhma, Ismu Rini Dwi Ari, I. Nyoman Suluh Wijaya

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Corporate Social Responsibility (CSR) programme in Pantai Harapan Jaya village is cultivation of mangrove and fishery capital distribution, to achieve the goal the CSR programme needed participation from the society in it. Moeliono in Fahrudin (2011) mentioned that participation from society is based by intrinsic reason from inside people it self and extrinsic reason from the other who related to him or from connection with other people. The fundamental connection who caused more boundaries from action which the organization can do called the social structure. The purpose of this research is to know the form of public participation and the density of the villager and people who is participated in CSR programme. This research use Social Network Analysis method by knew the Rate of Participation and Density. The result of the research is people who is involved in the programme is lived in Dusun Pondok Dua and they work in fisheries field. Rate of Participation is 11,61 and that means people involved in 11 or 12 activites of CSR Programme. The rate of participation of CSR Programme is categorized as high rate participation. The density value from the participant is 0.516 it’s mean that 51.6% of the people that participated is involved in the same step of CSR programme.

Keywords: community participation, social network analysis, corporate social responsibility, urban and regional studies

Procedia PDF Downloads 519

Authors: Matteo Gentilucci, Marco Materazzi, Gilberto Pambianchi

Abstract:

Climate change is an increasingly central issue in the world, because it affects many of human activities. In this context regional studies are of great importance because they sometimes differ from the general trend. This research focuses on a small area of central Italy which overlooks the Adriatic Sea, the province of Macerata. The aim is to analyze space-based climate changes, for precipitation and temperatures, in the last 3 climatological standard normals (1961-1990; 1971-2000; 1981-2010) through GIS software. The data collected from 30 weather stations for temperature and 61 rain gauges for precipitation were subject to quality controls: validation and homogenization. These data were fundamental for the spatialization of the variables (temperature and precipitation) through geostatistical techniques. To assess the best geostatistical technique for interpolation, the results of cross correlation were used. The co-kriging method with altitude as independent variable produced the best cross validation results for all time periods, among the methods analysed, with 'root mean square error standardized' close to 1, 'mean standardized error' close to 0, 'average standard error' and 'root mean square error' with similar values. The maps resulting from the analysis were compared by subtraction between rasters, producing 3 maps of annual variation and three other maps for each month of the year (1961/1990-1971/2000; 1971/2000-1981/2010; 1961/1990-1981/2010). The results show an increase in average annual temperature of about 0.1°C between 1961-1990 and 1971-2000 and 0.6 °C between 1961-1990 and 1981-2010. Instead annual precipitation shows an opposite trend, with an average difference from 1961-1990 to 1971-2000 of about 35 mm and from 1961-1990 to 1981-2010 of about 60 mm. Furthermore, the differences in the areas have been highlighted with area graphs and summarized in several tables as descriptive analysis. In fact for temperature between 1961-1990 and 1971-2000 the most areally represented frequency is 0.08°C (77.04 Km² on a total of about 2800 km²) with a kurtosis of 3.95 and a skewness of 2.19. Instead, the differences for temperatures from 1961-1990 to 1981-2010 show a most areally represented frequency of 0.83 °C, with -0.45 as kurtosis and 0.92 as skewness (36.9 km²). Therefore it can be said that distribution is more pointed for 1961/1990-1971/2000 and smoother but more intense in the growth for 1961/1990-1981/2010. In contrast, precipitation shows a very similar shape of distribution, although with different intensities, for both variations periods (first period 1961/1990-1971/2000 and second one 1961/1990-1981/2010) with similar values of kurtosis (1st = 1.93; 2nd = 1.34), skewness (1st = 1.81; 2nd = 1.62 for the second) and area of the most represented frequency (1st = 60.72 km²; 2nd = 52.80 km²). In conclusion, this methodology of analysis allows the assessment of small scale climate change for each month of the year and could be further investigated in relation to regional atmospheric dynamics.

Keywords: climate change, GIS, interpolation, co-kriging

Procedia PDF Downloads 130

Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

Procedia PDF Downloads 313

Authors: Azim Khodadadi, Sahar Sadaat Vakili, Ebrahim Babaei

Abstract:

This study presents a numerical method to optimize the failure rate and repair time of a typical radial distribution system. Failure rate and repair time are effective parameters in customer and energy based indices of reliability. Decrease of these parameters improves reliability indices. Thus, system stability will be boost. The penalty functions indirectly reflect the cost of investment which spent to improve these indices. Constraints on customer and energy based indices, i.e. SAIFI, SAIDI, CAIDI and AENS have been considered by using a new method which reduces optimization algorithm controlling parameters. Imperialist Competitive Algorithm (ICA) used as main optimization technique and particle swarm optimization (PSO), simulated annealing (SA) and differential evolution (DE) has been applied for further investigation. These algorithms have been implemented on a test system by MATLAB. Obtained results have been compared with each other. The optimized values of repair time and failure rate are much lower than current values which this achievement reduced investment cost and also ICA gives better answer than the other used algorithms.

Keywords: imperialist competitive algorithm, failure rate, repair time, radial distribution network

Procedia PDF Downloads 669

Authors: Khalid Mahmud

Abstract:

In this paper, an analytic approach is presented to evaluate the Bit Error Rate (BER) and round trip distance for a UWB chipless RFID system using diversity technique at the reader receiver using different modulation technique. The analysis is carried out with multiresonator based chipless RFID tags using frequency range from 3 GHz − 6 GHz and bandwidth of 500 M Hz in outdoor non-line-of-sight (NLOS) environment. SISO configuration is used to communicate from the reader to the tag and SIMO configuration is used do vice versa. Maximal Ratio Combining (MRC) technique is used in the reader. MPSK, DQPSK, DBPSK, BPSK, QPSK and DMPSK modulation techniques are considered with coherent demodulation to evaluate the BER performance. From the numerical analysis of the results, it is found that at a given BER maximum possible round trip distance can be achieved using DMPSK modulation technique. In addition, it has been proved that, while using DMPSK modulation technique, the application of diversity has very little effect on the overall improvement in reader receiver sensitivity and achievable distance. Finally the method not only proves to be a very good way for tag detection in case of a chipless RFID system but also gives a clear insight regarding the interrelationship between BER, read range, reader received power, number of receiving antenna in outdoor NLOS environment.

Keywords: EGC, MRC, BER, read range, diversity

Procedia PDF Downloads 352

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 267