Search results for: simulation modeling

Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

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In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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Authors: George Hadjinicola, Andreas Soteriou

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This paper examines the relationship between the number of price promotions that a firm should conduct per year and the level of safety stocks that the firm should maintain. Price promotions result in temporary sales increases, which affect the operations function through (1) an increase in the quantities demanded and (2) an increase in safety stocks required to maintain the desired service level. We propose a modeling framework where both price promotions and improved service levels, operationalized through higher safety stocks, can affect sales. We treat the annual number of promotions as a decision variable. We identify market conditions where the operations function, through improved safety stocks, can complement price promotions or even play the leading role in sales increases.

Keywords: price promotions, safety stocks, marketing/operations interface, mathematical model

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Authors: A. Benbouali, H. Saidi, A. Derrouazin, T. Bessaad

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Aerial robotics is a very exciting research field dealing with a variety of subjects, including the attitude control. This paper deals with the control of a four rotor vertical take-off and landing (VTOL) Unmanned Aerial Vehicle. The paper presents a mathematical model based on the approach of Lagrange for the flight control of an autonomous quad-rotor. It also describes the controller architecture which is based on PID regulators. The control method has been simulated in closed loop in different situations. All the calculation stages and the simulation results have been detailed.

Keywords: quad-rotor, lagrange approach, proportional integral derivate (PID) controller, Matlab/Simulink

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Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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Authors: Duhania O. Mahara, Santi W. Purnami, Aulia N. Fitria, Merissa N. Z. Wirontono, Revina Musfiroh, Shofi Andari, Sagiran Sagiran, Estiana Khoirunnisa, Wahyudi Widada

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For assessing interventions in numerous disease areas, the use of multiple time-to-event outcomes is common. An individual might experience two different events called bivariate time-to-event data, the events may be correlated because it come from the same subject and also influenced by individual characteristics. The bivariate time-to-event case can be applied by copula-based bivariate Cox survival model, using the Clayton and Frank copulas to analyze the dependence structure of each event and also the covariates effect. By applying this method to modeling the recurrent event infection of hemodialysis insertion on chronic kidney disease (CKD) patients, from the AIC and BIC values we find that the Clayton copula model was the best model with Kendall’s Tau is (τ=0,02).

Keywords: bivariate cox, bivariate event, copula function, survival copula

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Authors: Abdelazim Makki Ibrahim, Esamaldeen Ali

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This study aims at analysing the load settlement behavior and predict the bearing capacity of piled raft foundation a series of finite element models with different foundation configurations and stiffness were established. Numerical modeling is used to study the behavior of the piled raft foundation due to the complexity of piles, raft, and soil interaction and also due to the lack of reliable analytical method that can predict the behavior of the piled raft foundation system. Simple analytical models are developed to predict the average settlement and the load sharing between the piles and the raft in piled raft foundation system. A simple example to demonstrate the applications of these charts is included.

Keywords: finite element, pile-raft foundation, method, PLAXIS software, settlement

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Authors: Chahrazed Bendenia, Souhila Bendenia, Samia Moulebhar, Hanaa Merad-Dib, Sarra Merabet, Sid Ahmed Khantar, Baghdad Hadri

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In recent years, organic solar cells (OSCs) have become the fundamental concern of researchers thanks to their advantages in terms of flexibility, manufacturing processes and low cost. The performance of these devices is influenced by various factors, such as the layers introduced in the stacking of the solar cell realized. In our work, the modeling of a reverse OSC under AM1.5G illumination will be determined. The photo-active polymer/fullerene layer will be analyzed from the polymer variation of this layer using the SCAPS simulator to extract the J-V characteristics: open circuit voltage (Voc), short circuit current (Jsc), filling factor (FF) and power conversion efficiency (η). The results obtained indicated that the materials used have a significant impact on improving the photovoltaic parameters of the devices studied.

Keywords: solar, polymer, simulator, characteristics

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Authors: Ioana Neamtu

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This paper investigates the potential for demand-side management for the system price in the Nordic electricity market and the price effects of introducing wind-power into the system. The model proposed accounts for the micro-structure of the Nordic electricity market by modeling each hour individually, while still accounting for the relationship between the hours within a day. This flexibility allows us to explore the differences between peak and shoulder demand hours. Preliminary results show potential for demand response management, as indicated by the price elasticity of demand as well as a small but statistically significant decrease in price, given by the wind power penetration. Moreover, our study shows that these effects are stronger during day-time and peak hours,compared to night-time and shoulder hours.

Keywords: structural model, GMM estimation, system of equations, electricity market

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Authors: Dean A. McCorkle, Ed W. Hellman, Rebekka M. Dudensing, Dan D. Hanselka

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The motivation for this study centers on the labor- and cost-intensive nature of wine and table grape production in the U.S., and the potential opportunities for precision mechanization using robotics to augment those production tasks that are labor-intensive. The objectives of this study are to evaluate the economic viability of grape production in five U.S. states under current operating conditions, identify common production challenges and tasks that could be augmented with new technology, and quantify a maximum price for new technology that growers would be able to pay. Wine and table grape production is primed for precision mechanization technology as it faces a variety of production and labor issues. Methodology: Using a grower panel process, this project includes the development of a representative wine grape vineyard in five states and a representative table grape vineyard in California. The panels provided production, budget, and financial-related information that are typical for vineyards in their area. Labor costs for various production tasks are of particular interest. Using the data from the representative budget, 10-year projected financial statements have been developed for the representative vineyard and evaluated using a stochastic simulation model approach. Labor costs for selected vineyard production tasks were evaluated for the potential of new precision mechanization technology being developed. These tasks were selected based on a variety of factors, including input from the panel members, and the extent to which the development of new technology was deemed to be feasible. The net present value (NPV) of the labor cost over seven years for each production task was derived. This allowed for the calculation of a maximum price for new technology whereby the NPV of labor costs would equal the NPV of purchasing, owning, and operating new technology. Expected Results: The results from the stochastic model will show the projected financial health of each representative vineyard over the 2015-2024 timeframe. Investigators have developed a preliminary list of production tasks that have the potential for precision mechanization. For each task, the labor requirements, labor costs, and the maximum price for new technology will be presented and discussed. Together, these results will allow technology developers to focus and prioritize their research and development efforts for wine and table grape vineyards, and suggest opportunities to strengthen vineyard profitability and long-term viability using precision mechanization.

Keywords: net present value, robotic technology, stochastic simulation, wine and table grapes

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Authors: Abdelhalim Kessal, Ali Chebabhi

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In this paper, a controller based on fuzzy logic control (FLC) associated to Three Dimensional Space Vector Modulation (3DSVM) is applied for shunt active filter in αβo axes domain. The main goals are to improve power quality under disturbed loads, minimize source currents harmonics and reduce neutral current magnitude in the four-wire structure. FLC is used to obtain the reference current and control the DC-bus voltage at the inverter output. The switching signals of the four-leg inverter are generating through a Three Dimensional Space Vector Modulation (3DSVM). Selected simulation results have been shown to validate the proposed system.

Keywords: flc, 3dsvm, sapf, harmonic, inverter

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Authors: Kadda Boumediene, Mohamed Bouzit

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The prediction of the flow around marine propellers and vessel hulls propeller interaction is one of the challenges of Computational fluid dynamics (CFD). The CFD has emerged as a potential tool in recent years and has promising applications. The objective of the current study is to predict the hydrodynamic performances of HSP marine propeller in open water and behind a vessel. The unsteady 3-D flow was modeled numerically along with respectively the K-ω standard and K-ω SST turbulence models for steady and unsteady cases. The hydrodynamic performances such us a torque and thrust coefficients and efficiency show good agreement with the experiment results.

Keywords: seiun maru propeller, steady, unstead, CFD, HSP

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Authors: Mahesh Chudasama, Harit Raval

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Conical sections and shells of metal plates manufactured by 3-roller conical bending process are widely used in the industries. The process is completed by first bending the metal plates statically and then dynamic roller bending sequentially. It is required to have an analytical model to get maximum bending force, for optimum design of the machine, for static bending stage. Analytical models assuming various stress conditions are considered and these analytical models are compared considering various parameters and reported in this paper. It is concluded from the study that for higher bottom roller inclination, the shear stress affects greatly to the static bending force whereas for lower bottom roller inclination it can be neglected.

Keywords: roller-bending, static-bending, stress-conditions, analytical-modeling

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Authors: Asish O. Mathew, Lewlyn L. R. Rodrigues

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The organizations in the knowledge economy era have recognized the importance of building knowledge assets for sustainable growth and development. In comparison to other industries, Information Technology (IT) enterprises, holds an edge in developing an effective Knowledge Management (KM) program, thanks to their in-house technological abilities. This paper tries to study the various knowledge-based incentive programs and its effect on Knowledge Sharing and Learning in the context of the Indian IT sector. A conceptual model is developed linking KM incentives, knowledge sharing, and learning. A questionnaire study is conducted to collect primary data from the knowledge workers of the IT organizations located in India. The data was analysed using Structural Equation Modeling using Partial Least Square method. The results show a strong influence of knowledge management incentives on knowledge sharing and an indirect influence on learning.

Keywords: knowledge management, knowledge management incentives, knowledge sharing, learning

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Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Ikechukwu Ndu

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This study examines the econometric modeling of the relation between discretionary accrual earnings management, International Financial Reporting Standards (IFRS), and certain corporate governance factors with regard to listed Nigerian non-financial firms. Although discretionary accrual earnings management is a well-known and global problem that has an adverse impact on users of the financial statements, its relationship with IFRS and corporate governance is neither adequately researched nor properly systematically investigated in Nigeria. The dearth of research in the relation between discretionary accrual earnings management, IFRS and corporate governance in Nigeria has made it difficult for academics, practitioners, government setting bodies, regulators and international bodies to achieve a clearer understanding of how discretionary accrual earnings management relates to IFRS and certain corporate governance characteristics. This is the first study to the author’s best knowledge to date that makes interesting research contributions that significantly add to the literature of discretionary accrual earnings management and its relation with corporate governance and IFRS pertaining to the Nigerian context. A comprehensive review is undertaken of the literature of discretionary total accrual earnings management, IFRS, and certain corporate governance characteristics as well as the data, models, methodologies, and different estimators used in the study. Secondary financial statement, IFRS, and corporate governance data are sourced from Bloomberg database and published financial statements of Nigerian non-financial firms for the period 2004 to 2016. The methodology uses both the total and working capital accrual basis. This study has a number of interesting preliminary findings. First, there is a negative relationship between the level of discretionary accrual earnings management and the adoption of IFRS. However, this relationship does not appear to be statistically significant. Second, there is a significant negative relationship between the size of the board of directors and discretionary accrual earnings management. Third, CEO Separation of roles does not constrain earnings management, indicating the need to preserve relationships, personal connections, and maintain bonded friendships between the CEO, Chairman, and executive directors. Fourth, there is a significant negative relationship between discretionary accrual earnings management and the use of a Big Four firm as an auditor. Fifth, including shareholders in the audit committee, leads to a reduction in discretionary accrual earnings management. Sixth, the debt and return on assets (ROA) variables are significant and positively related to discretionary accrual earnings management. Finally, the company size variable indicated by the log of assets is surprisingly not found to be statistically significant and indicates that all Nigerian companies irrespective of size engage in discretionary accrual management. In conclusion, this study provides key insights that enable a better understanding of the relationship between discretionary accrual earnings management, IFRS, and corporate governance in the Nigerian context. It is expected that the results of this study will be of interest to academics, practitioners, regulators, governments, international bodies and other parties involved in policy setting and economic development in areas of financial reporting, securities regulation, accounting harmonization, and corporate governance.

Keywords: discretionary accrual earnings management, earnings manipulation, IFRS, corporate governance

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Authors: Luis Javier Serrano Tamayo

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This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method.

Keywords: analytic hierarchy process, multi-criteria decision-making, Pareto analysis, Colombian Marine Corps, projection operations, expert choice, amphibious landing ship

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Authors: Sherine Farouk, Fauzia Jabeen

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The purpose of this study is to examine the role played by ethical climate and CSR on organizational performance in public sector organizations. In particular, the research will shed light on the link between formalized ethical procedures and employee responses including corporate social responsibility, and organizational performance among public sector employees. Data was collected from 425 employees working in public sector organizations in Abu Dhabi, the capital of United Arab Emirates. Structural Equation Modeling will be used to test the proposed hypotheses. The paper contributes to the literature by being one of the first to study CSR and ethical climate within a Middle Eastern context, and will offer important implications for theory and practice.

Keywords: corporate social responsibility, ethical climate, organizational performance, United Arab Emirates

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Authors: Ahmed Soltan, Ahmed G. Radwan, Ahmed M. Soliman

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This work aims to generalize the integer order Sallen-Key filters into the fractional-order domain. The analysis in the case of two different fractional-order elements introduced where the general transfer function becomes four terms which are unusual in the conventional case. In addition, the effect of the transfer function parameters on the filter poles and hence the stability is introduced and closed forms for the filter critical frequencies are driven. Finally, different examples of the fractional order Sallen-Key filter design are presented with circuit simulations using ADS where a great matching between the numerical and simulation results is obtained.

Keywords: Sallen-Key, fractance, stability, low-pass filter, analog filter

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Authors: Barenten Suciu

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In this work, by replacing the traditional solid spokes with colloidal spokes, a vehicle wheel with a built-in suspension structure is proposed. Following the background and description of the wheel system, firstly, a vibration model of the wheel equipped with colloidal spokes is proposed, and based on such model the equivalent damping coefficients and spring constants are identified. Then, a modified model of a quarter-vehicle moving on a rough pavement is proposed in order to estimate the transmissibility of vibration from the road roughness to vehicle body. In the end, the optimal design of the colloidal spokes and the optimum number of colloidal spokes are decided in order to minimize the transmissibility of vibration, i.e., to maximize the ride comfort of the vehicle.

Keywords: built-in suspension, colloidal spoke, intrinsic spring, vibration analysis, wheel

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Authors: Samah Riache, Madjid Kidouche

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In this paper, we propose a nonlinear controller for Aerial Manipulator (AM) consists of a Quadrotor equipped with two degrees of freedom robotic arm. The kinematic and dynamic models were developed by considering the aerial manipulator as a coupled system. The proposed controller was designed using Nonsingular Terminal Sliding Mode Control. The objective of our approach is to improve performances and attenuate the chattering drawback using an adaptive algorithm in the discontinuous control part. Simulation results prove the effectiveness of the proposed control strategy compared with Sliding Mode Controller.

Keywords: adaptive algorithm, quadrotor, robotic arm, sliding mode control

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Authors: Boudjedra Abderrahim, Toumi Salah, Boutalbi Mostefa, Frihi Mohammed

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Nowadays, using the advancement of technology in semiconductor device fabrication, many transistors can be integrated to a single chip (VLSI). Although the growth chip density potentially eases systems-on-chip (SoCs) integrating thousands of processing element (PE) such as memory, processor, interfaces cores, system complexity, high-performance interconnect and scalable on-chip communication architecture become most challenges for many digital and embedded system designers. Networks-on-chip (NoCs) becomes a new paradigm that makes possible integrating heterogeneous devices and allows many communication constraints and performances. In this paper, we are interested for good performance and low area for implementation and a behavioral modeling of network on chip mesh topology design using VHDL hardware description language with performance evaluation and FPGA implementation results.

Keywords: design, implementation, communication system, network on chip, VHDL

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Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe

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The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.

Keywords: non-linear systems, fuzzy set Models, neural network, control law

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Authors: Jollen Dai, Truman You, Xinyun Du, Katrina Liu

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Transportation is one of the leading sources of greenhouse gas emissions (GHG). Thus, to meet the Paris Agreement 2015, all countries must adopt a different and more sustainable transportation system. From bikes to Maglev, the world is slowly shifting to sustainable transportation. To develop a utility public transit system, a sustainable web of buses must be implemented. As of now, only a handful of cities have adopted a detailed plan to implement a full fleet of e-buses by the 2030s, with Shenzhen in the lead. Every change requires a detailed plan and a focused analysis of the impacts of the change. In this report, the economic implications and financial implications have been taken into consideration to develop a well-rounded 10-year plan for New York City. We also apply the same financial model to the other cities, LA and Chicago. We picked NYC, Chicago, and LA to conduct the comparative NPB analysis since they are all big metropolitan cities and have complex transportation systems. All three cities have started an action plan to achieve a full fleet of e-bus in the decades. Plus, their energy carbon footprint and their energy price are very different, which are the key factors to the benefits of electric buses. Using TCO (Total Cost Ownership) financial analysis, we developed a model to calculate NPB (Net Present Benefit) /and compare EBS (electric buses) to DBS (diesel buses). We have considered all essential aspects in our model: initial investment, including the cost of a bus, charger, and installation, government fund (federal, state, local), labor cost, energy (electricity or diesel) cost, maintenance cost, insurance cost, health and environment benefit, and V2G (vehicle to grid) benefit. We see about $1,400,000 in benefits for a 12-year lifetime of an EBS compared to DBS provided the government fund to offset 50% of EBS purchase cost. With the government subsidy, an EBS starts to make positive cash flow in 5th year and can pay back its investment in 5 years. Please remember that in our model, we consider environmental and health benefits, and every year, $50,000 is counted as health benefits per bus. Besides health benefits, the significant benefits come from the energy cost savings and maintenance savings, which are about $600,000 and $200,000 in 12-year life cycle. Using linear regression, given certain budget limitations, we then designed an optimal three-phase process to replace all NYC electric buses in 10 years, i.e., by 2033. The linear regression process is to minimize the total cost over the years and have the lowest environmental cost. The overall benefits to replace all DBS with EBS for NYC is over $2.1 billion by the year of 2033. For LA, and Chicago, the benefits for electrification of the current bus fleet are $1.04 billion and $634 million by 2033. All NPB analyses and the algorithm to optimize the electrification phase process are implemented in Python code and can be shared.

Keywords: financial modeling, total cost ownership, net present benefits, electric bus, diesel bus, NYC, LA, Chicago

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Authors: Marwa Djebbi, Hakim Gabtni

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Gravity is a continuously advancing method that has become a mature technology for geological studies. Increasingly, it has been used to complement and constrain traditional seismic data and even used as the only tool to get information of the sub-surface. In fact, in some regions the seismic data, if available, are of poor quality and hard to be interpreted. Such is the case for the current study area. The Nefza zone is part of the Tellian fold and thrust belt domain in the north west of Tunisia. It is essentially made of a pile of allochthonous units resulting from a major Neogene tectonic event. Its tectonic and stratigraphic developments have always been subject of controversies. Considering the geological and hydrogeological importance of this area, a detailed interdisciplinary study has been conducted integrating geology, seismic and gravity techniques. The interpretation of Gravity data allowed the delimitation of the dune reservoir and the identification of the regional lineaments contouring the area. It revealed the presence of three gravity lows that correspond to the dune of Zouara and Ouchtata separated along with a positive gravity axis espousing the Ain Allega_Aroub Er Roumane axe. The Bouguer gravity map illustrated the compartmentalization of the Zouara dune into two depressions separated by a NW-SE anomaly trend. This constitution was confirmed by the vertical derivative map which showed the individualization of two depressions with slightly different anomaly values. The horizontal gravity gradient magnitude was performed in order to determine the different geological features present in the studied area. The latest indicated the presence of NE-SW parallel folds according to the major Atlasic direction. Also, NW-SE and EW trends were identified. The maxima tracing confirmed this direction by the presence of NE-SW faults, mainly the Ghardimaou_Cap Serrat accident. The quality of the available seismic sections and the absence of borehole data in the region, except few hydraulic wells that been drilled and showing the heterogeneity of the substratum of the dune, required the process of gravity modeling of this challenging area that necessitates to be modeled for the geometrical characterization of the dune reservoir and determine the different stratigraphic series underneath these deposits. For more detailed and accurate results, the scale of study will be reduced in coming research. A more concise method will be elaborated; the 4D microgravity survey. This approach is considered as an expansion of gravity method and its fourth dimension is time. It will allow a continuous and repeated monitoring of fluid movement in the subsurface according to the micro gal (μgall) scale. The gravity effect is a result of a monthly variation of the dynamic groundwater level which correlates with rainfall during different periods.

Keywords: 3D gravity modeling, dune reservoir, heterogeneous substratum, seismic interpretation

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Authors: Abhisek Chakrabarty, Subhraprakash Mandal

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Flash flood is one of the catastrophic natural hazards in the mountainous region of India. The recent flood in the Mandakini River in Kedarnath (14-17th June, 2013) is a classic example of flash floods that devastated Uttarakhand by killing thousands of people.The disaster was an integrated effect of high intensityrainfall, sudden breach of Chorabari Lake and very steep topography. Every year in Himalayan Region flash flood occur due to intense rainfall over a short period of time, cloud burst, glacial lake outburst and collapse of artificial check dam that cause high flow of river water. In Sikkim-Derjeeling Himalaya one of the probable flash flood occurrence zone is Teesta Watershed. The Teesta River is a right tributary of the Brahmaputra with draining mountain area of approximately 8600 Sq. km. It originates in the Pauhunri massif (7127 m). The total length of the mountain section of the river amounts to 182 km. The Teesta is characterized by a complex hydrological regime. The river is fed not only by precipitation, but also by melting glaciers and snow as well as groundwater. The present study describes an attempt to model surface runoff in upper Teesta basin, which is directly related to catastrophic flood events, by creating a system based on GIS technology. The main object was to construct a direct unit hydrograph for an excess rainfall by estimating the stream flow response at the outlet of a watershed. Specifically, the methodology was based on the creation of a spatial database in GIS environment and on data editing. Moreover, rainfall time-series data collected from Indian Meteorological Department and they were processed in order to calculate flow time and the runoff volume. Apart from the meteorological data, background data such as topography, drainage network, land cover and geological data were also collected. Clipping the watershed from the entire area and the streamline generation for Teesta watershed were done and cross-sectional profiles plotted across the river at various locations from Aster DEM data using the ERDAS IMAGINE 9.0 and Arc GIS 10.0 software. The analysis of different hydraulic model to detect flash flood probability ware done using HEC-RAS, Flow-2D, HEC-HMS Software, which were of great importance in order to achieve the final result. With an input rainfall intensity above 400 mm per day for three days the flood runoff simulation models shows outbursts of lakes and check dam individually or in combination with run-off causing severe damage to the downstream settlements. Model output shows that 313 Sq. km area were found to be most vulnerable to flash flood includes Melli, Jourthang, Chungthang, and Lachung and 655sq. km. as moderately vulnerable includes Rangpo,Yathang, Dambung,Bardang, Singtam, Teesta Bazarand Thangu Valley. The model was validated by inserting the rain fall data of a flood event took place in August 1968, and 78% of the actual area flooded reflected in the output of the model. Lastly preventive and curative measures were suggested to reduce the losses by probable flash flood event.

Keywords: flash flood, GIS, runoff, simulation model, Teesta river basin

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

Abstract:

Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

Procedia PDF Downloads 142

Authors: Morteza Esfandiari, Shabnam Jabari, Heather MacGrath, David Coleman

Abstract:

Flood is a severe issue in different places in the world as well as the city of Fredericton, New Brunswick, Canada. The downtown area of Fredericton is close to the Saint John River, which is susceptible to flood around May every year. Recently, the frequency of flooding seems to be increased, especially after the fact that the downtown area and surrounding urban/agricultural lands got flooded in two consecutive years in 2018 and 2019. In order to have an explicit vision of flood span and damage to affected areas, it is necessary to use either flood inundation modelling or satellite data. Due to contingent availability and weather dependency of optical satellites, and limited existing data for the high cost of hydrodynamic models, it is not always feasible to rely on these sources of data to generate quality flood maps after or during the catastrophe. Height Above the Nearest Drainage (HAND), a state-of-the-art topo-hydrological index, normalizes the height of a basin based on the relative elevation along with the stream network and specifies the gravitational or the relative drainage potential of an area. HAND is a relative height difference between the stream network and each cell on a Digital Terrain Model (DTM). The stream layer is provided through a multi-step, time-consuming process which does not always result in an optimal representation of the river centerline depending on the topographic complexity of that region. HAND is used in numerous case studies with quite acceptable and sometimes unexpected results because of natural and human-made features on the surface of the earth. Some of these features might cause a disturbance in the generated model, and consequently, the model might not be able to predict the flow simulation accurately. We propose to include a previously existing stream layer generated by the province of New Brunswick and benefit from culvert maps to improve the water flow simulation and accordingly the accuracy of HAND model. By considering these parameters in our processing, we were able to increase the accuracy of the model from nearly 74% to almost 92%. The improved model can be used for generating highly accurate flood maps, which is necessary for future urban planning and flood damage estimation without any need for satellite imagery or hydrodynamic computations.

Keywords: HAND, DTM, rapid floodplain, simplified conceptual models

Procedia PDF Downloads 151

Authors: Janjira Triped, Wipada Sanongraj, Wipawee Khamwichit

Abstract:

The research work covered in this study includes the morphological structure and optical properties of TiO2-coated silk fibroin (SF) filters at 2.5% wt. TiO2/vol. PVA solution. SEM micrographs revealed the fibrous morphology of the TiO2-coated SF filters. An average diameter of the SF fiber was estimated to be approximately 10µm. Also, it was confirmed that TiO2 can be adhered more on SF filter surface at higher TiO2 dosages. The activity of semiconductor materials was studied by UV-VIS spectrophotometer method. The spectral data recorded shows the strong cut off at 390 nm. The calculated band-gap energy was about 3.19 eV. The photocatalytic activity of the filter was tested for gaseous formaldehyde removal in a modeling room with the total volume of 2.66 m3. The highest removal efficiency (54.72 ± 1.75%) was obtained at the initial formaldehyde concentration of about 5.00 ± 0.50ppm.

Keywords: photocatalytic oxidation process, formaldehyde (HCHO), silk fibroin (SF), titanium dioxide (TiO2)

Procedia PDF Downloads 469

Authors: Alireza Nikbakht Shahbazi, Emadeddin Shirali

Abstract:

Since optimization issues of water resources are complicated due to the variety of decision making criteria and objective functions, it is sometimes impossible to resolve them through regular optimization methods or, it is time or money consuming. Therefore, the use of modern tools and methods is inevitable in resolving such problems. An accurate and essential utilization policy has to be determined in order to use natural resources such as water reservoirs optimally. Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The basic information applied in water reservoir programming studies generally include meteorological, hydrological, agricultural and water reservoir related data, and the geometric characteristics of the reservoir. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As a meta-exploratory method, genetic algorithm was applied in order to provide utilization rule curves (intersecting the reservoir volume). MATLAB software was used in order to resolve the foresaid model. Rule curves were firstly obtained through genetic algorithm. Then the significance of using rule curves and the decrease in decision making variables in the system was determined through system simulation and comparing the results with optimization results (Standard Operating Procedure). One of the most essential issues in optimization of a complicated water resource system is the increasing number of variables. Therefore a lot of time is required to find an optimum answer and in some cases, no desirable result is obtained. In this research, intersecting the reservoir volume has been applied as a modern model in order to reduce the number of variables. Water reservoir programming studies has been performed based on basic information, general hypotheses and standards and applying monthly simulation technique for a statistical period of 30 years. Results indicated that application of rule curve prevents the extreme shortages and decrease the monthly shortages.

Keywords: optimization, rule curve, genetic algorithm method, Dez dam reservoir

Procedia PDF Downloads 265