Search results for: Autoregressive Integrated Moving Average

Authors: A. Mansouri, F. Krim

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This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

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Authors: Navid Daryasafar, Nima Farshidfar

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In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

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Authors: Jia-Jang Wu

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The objective of this research is to develop a general technique so that one may predict the dynamic behaviour of a three-dimensional scale crane model subjected to time-dependent moving point forces by means of conventional finite element computer packages. To this end, the whole scale crane model is divided into two parts: the stationary framework and the moving substructure. In such a case, the dynamic responses of a scale crane model can be predicted from the forced vibration responses of the stationary framework due to actions of the four time-dependent moving point forces induced by the moving substructure. Since the magnitudes and positions of the moving point forces are dependent on the relative positions between the trolley, moving substructure and the stationary framework, it can be found from the numerical results that the time histories for the moving speeds of the moving substructure and the trolley are the key factors affecting the dynamic responses of the scale crane model.

Keywords: moving load, moving substructure, dynamic responses, forced vibration responses

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Authors: Deva Kanta Phukan

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An attempt is made where an electrically conducting fluid is injected from a fixed outer cylindrical casing onto an inner moving cylindrical rod. A magnetic field is applied parallel to the axis of the cylindrical rod. The basic governing set of partial differential equations for conservation of mass and momentum are reduced to a set of non-linear ordinary differential equation by introducing similarity transformation, which are integrated numerically. A perturbation solution for the case of large magnetic parameter is derived for constant Reynolds number.

Keywords: annular axi-symmetric stagnation flow, conducting fluid, magnetic field, moving cylinder

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Authors: Haritha Saranga

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Service quality has become an important driver of competition in manufacturing industries of late, as many products are being sold in conjunction with service offerings. With increase in computational power and data capture capabilities, it has become possible to analyze and estimate various aspects of service quality at the granular level and determine their impact on business performance. In the current study context, dealer level, model-wise warranty data from one of the top two-wheeler manufacturers in India is used to estimate service quality of individual dealers and its impact on warranty related costs and sales performance. We collected primary data on warranty costs, number of complaints, monthly sales, type of quality upgrades, etc. from the two-wheeler automaker. In addition, we gathered secondary data on various regions in India, such as petrol and diesel prices, geographic and climatic conditions of various regions where the dealers are located, to control for customer usage patterns. We analyze this primary and secondary data with the help of a variety of analytics tools such as Auto-Regressive Integrated Moving Average (ARIMA), Seasonal ARIMA and ARIMAX. Study results, after controlling for a variety of factors, such as size, age, region of the dealership, and customer usage pattern, show that service quality does influence sales of the products in a significant manner. A more nuanced analysis reveals the dynamics between product quality and service quality, and how their interaction affects sales performance in the Indian two-wheeler industry context. We also provide various managerial insights using descriptive analytics and build a model that can provide sales projections using a variety of forecasting techniques.

Keywords: service quality, product quality, automobile industry, business analytics, auto-regressive integrated moving average

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Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

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Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

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Authors: Petra Dilling

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This study examines the market reaction to the publication of integrated reports for a sample of 316 global companies for the reporting year 2018. Applying event study methodology, we find significant cumulative average abnormal returns (CAARs) after the publication date. To ensure robust estimation resultsthe three-factor model, according to Fama and French, is used as well as a market-adjusted model, a CAPM and a Frama-French model taking GARCH effects into account. We find a significant positive CAAR after the publication day of the integrated report. Our results suggest that investors react to information provided in the integrated report and that they react differently to the annual financial report. Furthermore, our cross-sectional analysis confirms that companies with a significant positive cumulative average abnormal show certain characteristic. It was found that European companies have a higher likelihood to experience a stronger significant positive market reaction to their integrated report publication.

Keywords: integrated report, event methodology, cumulative abnormal return, sustainability, CAPM

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Authors: B. G. Abiona

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This study compared profitability analysis of integrated and non-integrated fish farming in Ogun State, Nigeria. Primary data were collected using interview guide. Random sampling techniques was used to select 133 non-integrated fish farmers (NIFF) and 216 integrated fish farmers (IFF) (n = 349) from the study area. Data were analyzed using Chi-square, T-test and Pearson Product moment correlation. Results showed that 92.5% of NIFF was male compared to IFF (90.7%). Also, 96.8% of IFF and 79.7% of NIFF were married. The mean ages of sampled farmers were 44 years (NIFF) and 46 years (IFF) while the mean fish farming experiences were 4 years (NIFF) and 5 years (IFF). Also, the average net profit per year of integrated fish farmers was ₦162,550 compared to NIFF (₦61,638). The chi-square analyses showed that knowledge of fish farming had significant relationship with respondents sex (χ2 = 9.44, df = 2, p < 0.05), age (r = 0.20, p< 0.05) and farming experience (r = p = 0.05). Significant differences exist between integrated and non-integrated fish farming, considering their knowledge of fish farming (t = 21.5, χ = 43.01, p < 0.05). The study concluded that IFF are more profitable compared to NIFF. It was recommended that private investors and NGOs should sponsor short training and courses which will enhance efficiency of fish farming to boost productivity among fish farmers.

Keywords: profitability analysis, farms, integration

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Authors: Raymond K. Dziwornu

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Lending rate of agriculture loan has persistently been high and attributed to risk in the sector. This study examined how food inflation and agriculture lending rate react to each other in Ghana using vector autoregressive approach. Quarterly data from 2006 to 2018 was obtained from the Bank of Ghana quarterly bulletin and the Ghana Statistical Service reports. The study found that a positive standard deviation shock to food inflation causes lending rate of agriculture loan to react negatively in the short run, but positively and steadily in the long run. This suggests the need to direct appropriate policy measures to reduce food inflation and consequently, the cost of credit to the agricultural sector for its growth.

Keywords: food inflation, agriculture, lending rate, vector autoregressive, Ghana

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Authors: A. E. El-Henawey, A. A. El-Kouny, M. M. Abd –El-Halim

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Moving target indication (MTI) which is an anti-clutter technique that limits the display of clutter echoes. It uses the radar received information primarily to display moving targets only. The purpose of MTI is to discriminate moving targets from a background of clutter or slowly-moving chaff particles as shown in this paper. Processing system in these radars is so massive and complex; since it is supposed to perform a great amount of processing in very short time, in most radar applications the response of a single canceler is not acceptable since it does not have a wide notch in the stop-band. A double-delay canceler is an MTI delay-line canceler employing the two-delay-line configuration to improve the performance by widening the clutter-rejection notches, as compared with single-delay cancelers. This canceler is also called a double canceler, dual-delay canceler, or three-pulse canceler. In this paper, a double delay line canceler is chosen for study due to its simplicity in both concept and implementation. Discussing the implementation of a simple digital moving target indicator (DMTI) using FPGA which has distinct advantages compared to other application specific integrated circuit (ASIC) for the purposes of this work. The FPGA provides flexibility and stability which are important factors in the radar application.

Keywords: FPGA, MTI, double delay line canceler, Doppler Shift

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Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

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The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

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Authors: M. Karimpour, N. Elkhoury, L. Hitihamillage, S. Moridpour, R. Hesami

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There is a necessity among rail transportation authorities for a superior understanding of the rail track degradation overtime and the factors influencing rail degradation. They need an accurate technique to identify the time when rail tracks fail or need maintenance. In turn, this will help to increase the level of safety and comfort of the passengers and the vehicles as well as improve the cost effectiveness of maintenance activities. An accurate model can play a key role in prediction of the long-term behaviour of railroad tracks. An accurate model can decrease the cost of maintenance. In this research, the rail track degradation is predicted using an autoregressive moving average with exogenous input (ARMAX). An ARMAX has been implemented on Melbourne tram data to estimate the values for the tram track degradation. Gauge values and rail usage in Million Gross Tone (MGT) are the main parameters used in the model. The developed model can accurately predict the future status of the tram tracks.

Keywords: ARMAX, dynamic systems, MGT, prediction, rail degradation

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Authors: Umar Farouk Abbas, Danjuma Mustapha, Hamisu Idi

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It is now a known fact that quality is an important issue in manufacturing industries. A control chart is an integrated and powerful tool in statistical process control (SPC). The mean µ and standard deviation σ parameters are estimated. In general, the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) are used in the detection of small shifts in joint monitoring of several correlated variables; the charts used information from past data which makes them sensitive to small shifts. The aim of the paper is to compare the performance of Shewhart xbar, MEWMA, and MCUSUM control charts in terms of their false rates when parameters are estimated with autocorrelation. A simulation was conducted in R software to generate the average run length (ARL) values of each of the charts. After the analysis, the results show that a comparison of the false alarm rates of the charts shows that MEWMA chart has lower false alarm rates than the MCUSUM chart at various levels of parameter estimated to the number of ARL0 (in control) values. Also noticed was that the sample size has an advert effect on the false alarm of the control charts.

Keywords: average run length, MCUSUM chart, MEWMA chart, false alarm rate, parameter estimation, simulation

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Firooz Bakhtiari-Nejad, Hamidreza Rostami, Meysam Mirzaee, Mona Zandbaf

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Dynamic tests are an important step of the design of engineering structures, because the accuracy of predictions of theoretical–numerical procedures can be assessed. In experimental test of moving loads that is one of the major research topics, the load is modeled as a simple moving mass or a small vehicle. This paper deals with the applicability of Non-Contact Moving Load (NML) for vibration analysis. For this purpose, an experimental set-up is designed to generate the different types of NML including constant and harmonic. The proposed method relies on pressurized air which is useful, especially when dealing with fragile or sensitive structures. To demonstrate the performance of this system, the set-up is employed for a modal analysis of a beam and detecting crack of the beam. The obtained results indicate that the experimental set-up for NML can be an attractive alternative to the moving load problems.

Keywords: experimental analysis, moving load, non-contact excitation, materials engineering

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Authors: Fares Almomani, Majeda Khraisheh, Rahul Bhosale, Anand Kumar, Ujjal Gosh

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Septic tanks (STs) are very commonly used wastewater collection systems in the world especially in rural areas. In this study, the use of moving bed biological reactors (MBBR) for the treatment of septic tanks effluents (STE) was studied. The study was included treating septic tank effluent from one house hold using MBBRs. Significant ammonia removal rate was observed in all the reactors throughout the 180 days of operation suggesting that the MBBRs were successful in reducing the concentration of ammonia from septic tank effluent. The average ammonia removal rate at 25◦C for the reactor operated at hydraulic retention time of 5.7 hr (R1) was 0.540 kg-N/m3and for the reactor operated at hydraulic retention time of 13.3hr (R2) was 0.279 kg-N/m3. Ammonia removal rates were decreased to 0.3208 kg-N/m3 for R1 and 0.212 kg-N/m3 for R3 as the temperature of reactor was decreased to 8 ◦C. A strong correlation exists between theta model and the rates of ammonia removal for the reactors operated in continuous flow. The average ϴ values for the continuous flow reactors during the temperature change from 8°C to 20 °C were found to be 1.053±0.051. MBBR technology can be successfully used as a polishing treatment for septic tank effluent.

Keywords: septic tanks, wastewater treatment, morphology, moving biological reactors, nitrification

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Authors: Neslihan Genckal, Reha Gursoy, Vedat Z. Dogan

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In this study, dynamic responses of composite plates on elastic foundations subjected to impact and moving loads are investigated. The first order shear deformation (FSDT) theory is used for moderately thick plates. Pasternak-type (two-parameter) elastic foundation is assumed. Elastic foundation effects are integrated into the governing equations. It is assumed that plate is first hit by a mass as an impact type loading then the mass continues to move on the composite plate as a distributed moving loading, which resembles the aircraft landing on airport pavements. Impact and moving loadings are modeled by a mass-spring-damper system with a wheel. The wheel is assumed to be continuously in contact with the plate after impact. The governing partial differential equations of motion for displacements are converted into the ordinary differential equations in the time domain by using Galerkin’s method. Then, these sets of equations are solved by using the Runge-Kutta method. Several parameters such as vertical and horizontal velocities of the aircraft, volume fractions of the steel rebar in the reinforced concrete layer, and the different touchdown locations of the aircraft tire on the runway are considered in the numerical simulation. The results are compared with those of the ABAQUS, which is a commercial finite element code.

Keywords: elastic foundation, impact, moving load, thick plate

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Authors: Junior B. N. Adohinzin, Ling Xu

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Nitrogen is among the main nutrients encouraging the growth of organic matter and algae which cause eutrophication in water bodies. Therefore, its removal from wastewater has become a worldwide emerging concern. In this research, an innovative Membrane Bioreactor (MBR) system named “moving bed membrane bioreactor (MBMBR)” was developed and investigated under intermittently-aerated mode for simultaneous removal of organic carbon and nitrogen. Results indicated that the variation of the intermittently aerated duration did not have an apparent impact on COD and NH4+–N removal rate, yielding the effluent with average COD and NH4+–N removal efficiency of more than 92 and 91% respectively. However, in the intermittently aerated cycle of (continuously aeration/0s mix), (aeration 90s/mix 90s) and (aeration 90s/mix 180s); the average TN removal efficiency was 67.6%, 69.5% and 87.8% respectively. At the same time, their nitrite accumulation rate was 4.5%, 49.1% and 79.4% respectively. These results indicate that the intermittently aerated mode is an efficient way to controlling the nitrification to stop at nitrition; and also the length of anoxic duration is a key factor in improving TN removal.

Keywords: membrane bioreactor (MBR), moving bed biofilm reactor (MBBR), nutrients removal, simultaneous nitrification and denitrification

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Authors: Idowu Ibikunle Albert, Atilade Adesanya Oluwafemi, Okedeyi Abiodun Sikiru, Mustapha Rilwan Adewale

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These present-day all areas of transport have experienced large advances characterized by increases in the speeds and weight of vehicles. As a result, this paper considered the Transverse Vibration of an Elastic Beam Resting on a Variable Elastic Foundation Subjected to a moving Load. The beam is presumed to be uniformly distributed and has simple support at both ends. The moving distributed moving mass is assumed to move with constant velocity. The governing equations, which are fourth-order partial differential equations, were reduced to second-order partial differential equations using an analytical method in terms of series solution and solved by a numerical method using mathematical software (Maple). Results show that an increase in the values of beam parameters, moving Mass M, and k-stiffness K, significantly reduces the deflection profile of the vibrating beam. In the results, it was equally found that moving mass is greater than moving force.

Keywords: elastic beam, moving load, response of structure, variable elastic foundation

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Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi

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The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.

Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control

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Authors: Jae Moon Lee

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In general, algorithms to find continuous k-nearest neighbors have been researched on the location based services, monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, this problem is when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. In this case, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under gaming environments.

Keywords: flocking behavior, heterogeneous agents, similarity, simulation

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Authors: Kalai Lamia, Jilani Faouzi

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Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behaviour of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.

Keywords: asymmetry volatility, clustering, stylised facts, leverage effect

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Authors: Khizir Mohd Ismail, Yu Jun Lim, Tshun Howe Yong

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The study of flow behavior in an enclosed volume using Computational Fluid Dynamics (CFD) has been around for decades. However, due to the knowledge limitation of adaptive grid methods, the flow in an enclosed volume near the moving wall using CFD is less explored. A CFD simulation of flow in an enclosed volume near a moving wall was demonstrated and studied by introducing a moving mesh method and was modeled with Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach. A static enclosed volume with controlled opening size in the bottom was positioned against a moving, translational wall with sliding mesh features. Controlled variables such as smoothed, crevices and corrugated wall characteristics, the distance between the enclosed volume to the wall and the moving wall speed against the enclosed chamber were varied to understand how the flow behaves and reacts in between these two geometries. These model simulations were validated against experimental results and provided result confidence when the simulation had shown good agreement with the experimental data. This study had provided better insight into the flow behaving in an enclosed volume when various wall types in motion were introduced within the various distance between each other and create a potential opportunity of application which involves adaptive grid methods in CFD.

Keywords: moving wall, adaptive grid methods, CFD, moving mesh method

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Authors: Xu Wang

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This research builds linear regressions of U.S. macroeconomic condition and volatility measures in the investment grade and high yield Credit Default Swap index spreads using monthly data from March 2009 to July 2016, to study the relationship between different dimensions of macroeconomy and overall credit risk quality. The most significant contribution of this research is systematically examining individual and joint effects of macroeconomic condition and volatility on CDX spreads by including macroeconomic time series that captures different dimensions of the U.S. economy. The industrial production index growth, non-farm payroll growth, consumer price index growth, 3-month treasury rate and consumer sentiment are introduced to capture the condition of real economic activity, employment, inflation, monetary policy and risk aversion respectively. The conditional variance of the macroeconomic series is constructed using ARMA-GARCH model and is used to measure macroeconomic volatility. The linear regression model is conducted to capture relationships between monthly average CDX spreads and macroeconomic variables. The Newey–West estimator is used to control for autocorrelation and heteroskedasticity in error terms. Furthermore, the sensitivity factor analysis and standardized coefficients analysis are conducted to compare the sensitivity of CDX spreads to different macroeconomic variables and to compare relative effects of macroeconomic condition versus macroeconomic uncertainty respectively. This research shows that macroeconomic condition can have a negative effect on CDX spread while macroeconomic volatility has a positive effect on determining CDX spread. Macroeconomic condition and volatility variables can jointly explain more than 70% of the whole variation of the CDX spread. In addition, sensitivity factor analysis shows that the CDX spread is the most sensitive to Consumer Sentiment index. Finally, the standardized coefficients analysis shows that both macroeconomic condition and volatility variables are important in determining CDX spread but macroeconomic condition category of variables have more relative importance in determining CDX spread than macroeconomic volatility category of variables. This research shows that the CDX spread can reflect the individual and joint effects of macroeconomic condition and volatility, which suggests that individual investors or government should carefully regard CDX spread as a measure of overall credit risk because the CDX spread is influenced by macroeconomy. In addition, the significance of macroeconomic condition and volatility variables, such as Non-farm Payroll growth rate and Industrial Production Index growth volatility suggests that the government, should pay more attention to the overall credit quality in the market when macroecnomy is low or volatile.

Keywords: autoregressive moving average model, credit spread puzzle, credit default swap spread, generalized autoregressive conditional heteroskedasticity model, macroeconomic conditions, macroeconomic uncertainty

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Authors: Shih-Chieh Liao, Jen-Ying Ma

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Dual protagonists game always bring a unique experience compared to the other games. This research wants to discuss whether the dual protagonists have the moving ability and special ability or not; it will affect the preference of the players. This research will focus on the single-player dual protagonists game. After the observation, we found that when players control the dual protagonists, the moving ability and special ability are a great point defining the preference of players. When players control the character, which is lack of moving ability, they often feel impatient with the inconvenient mechanism and then reduce the will to play with the character or even the game. Furthermore, the special ability is also important in the situation that there is another character to compare with. When the character is too powerful, players tend not to use the weaker one. In addition, gender is a big deal in the games. It surprisingly controls the will of play occasionally. In view of these, this research makes a single-player dual protagonists game and the dual protagonists are limited to male and female. The experiment content detected with Electrodermal Activity (EDA) includes seven different situations. (1) male and females both have the moving ability and special ability. (2) male and female both have a special ability, but female does not have the moving ability. (3) male and females both have a special ability, but the male does not have the moving ability. (4) male and female both have the moving ability, but the male does not have special ability (5) male and female both have the moving ability, but female does not have a special ability (6) male-only has the moving ability and female-only has a special ability (7) male-only has a special ability and female only has the moving ability. The experiment will evaluate the emotional changes of the subjects in those situations. The result sorted by the significance of player preference is (6)>(4)>(1)>(2)>(5)>(3)>(7). The result demonstrates that players prefer females with special abilities or males with moving abilities. The game developer could design the ability of dual protagonists based on this research. Therefore, players may have a better experience.

Keywords: biofeedback, dual protagonists, emotional responses, psychology, user experience

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Ziba Omidi, Min-Ki Kim

Abstract:

This research presents the design, fabrication and application of a flavor sensor for an integrated electronic tongue and electronic nose that can allow rapid characterization of multi-component mixtures in a solution. The odor gas and liquid are separated using hydrophobic porous membrane in micro fluidic channel. The sensor uses an array composed of microbeads in micromachined cavities localized on silicon wafer. Sensing occurs via colorimetric and fluorescence changes to receptors and indicator molecules that are attached to termination sites on the polymeric microbeads. As a result, the sensor array system enables simultaneous and near-real-time analyses using small samples and reagent volumes with the capacity to incorporate significant redundancies. One of the key parts of the system is a passive pump driven only by capillary force. The hydrophilic surface of the fluidic structure draws the sample into the sensor array without any moving mechanical parts. Since there is no moving mechanical component in the structure, the size of the fluidic structure can be compact and the fabrication becomes simple when compared to the device including active microfluidic components. These factors should make the proposed system inexpensive to mass-produce, portable and compatible with biomedical applications.

Keywords: optical sensor, semiconductor manufacturing, smell sensor, taste sensor

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

Abstract:

In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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Authors: Suparman Suparman

Abstract:

A white noise in autoregressive (AR) model is often assumed to be normally distributed. In application, the white noise usually do not follows a normal distribution. This paper aims to estimate a parameter of AR model that has a exponential white noise. A Bayesian method is adopted. A prior distribution of the parameter of AR model is selected and then this prior distribution is combined with a likelihood function of data to get a posterior distribution. Based on this posterior distribution, a Bayesian estimator for the parameter of AR model is estimated. Because the order of AR model is considered a parameter, this Bayesian estimator cannot be explicitly calculated. To resolve this problem, a method of reversible jump Markov Chain Monte Carlo (MCMC) is adopted. A result is a estimation of the parameter AR model can be simultaneously calculated.

Keywords: autoregressive (AR) model, exponential white Noise, bayesian, reversible jump Markov Chain Monte Carlo (MCMC)

Procedia PDF Downloads 320