Search results for: Time series modelling

Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Ismail Saritas, Sadiye Didem Boztepe Erkis, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modelled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the developed system, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), and fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: Artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: C. B. Vishwakarma

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The author presented a method for model order reduction of large-scale time-invariant systems in time domain. In this approach, two modified Hankel matrices are suggested for getting reduced order models. The proposed method is simple, efficient and retains stability feature of the original high order system. The viability of the method is illustrated through the examples taken from literature.

Keywords: Model Order Reduction, Stability, Hankel Matrix, Time-Domain, Integral Square Error.

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine.

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Authors: A. Habibizad Navin, A. Sadighi, M. Naghian Fesharaki, M. Mirnia, M. Teshnelab, R. Keshmiri

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This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.

Keywords: Data oriented modelling, image, clustering, segmentation, classification, ADBT and image processing.

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Authors: Shu Lü, Shouming Zhong, Zixin Liu

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In this paper, the robust exponential stability problem of discrete-time uncertain stochastic neural networks with timevarying delays is investigated. By introducing a new augmented Lyapunov function, some delay-dependent stable results are obtained in terms of linear matrix inequality (LMI) technique. Compared with some existing results in the literature, the conservatism of the new criteria is reduced notably. Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.

Keywords: Robust exponential stability, delay-dependent stability, discrete-time neural networks, stochastic, time-varying delays.

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Authors: Xiangbin Zhu

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EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.

Keywords: Fuzzy control, real-time systems, EDF, misdeadline ratio.

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Authors: Dimitra Alexiou

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During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: Tourism, statistical methods, exponential smoothing, land spatial planning, economy, Microsoft Excel.

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Authors: Fazeera Ujin, Kamran Shavarebi Ali, Zarina Yasmin Hanur Harith

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This research paper reports on the feasibility and viability of eggshells ash and its effects on the water content and setting time of cement. An experiment was carried out to determine the quantity of water required in order to follow standard cement paste of normal consistency in accordance with MS EN 196-3:2007. The eggshells ash passing the 90µm sieve was used in the investigation. Eggshells ash with percentage of 0%, 0.1%, 0.5%, 1.0%, 1.5% and 2.0% were constituted to replace the cement. Chemical properties of both eggshells ash and cement are compared. From the results obtained, both eggshells ash and cement have the same chemical composition and primary composition which is the calcium compounds. Results from the setting time show that by adding the eggshells ash to the cement, the setting time of the cement decreases. In short, the higher amount of eggshells ash, the faster the rate of setting and apply to all percentage of eggshells ash that were used in this investigation. Both initial and final setting times fulfill the setting time requirements by Malaysian Standard. Hence, it is suggested that eggshells ash can be used as an admixture in concrete mix.

Keywords: Construction Materials, Eggshells Ash, Solid Waste, Setting Time.

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Authors: Ali Ghaffari, A. Hosein Shamekhi, Akbar Saki, Ehsan Kamrani

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In order to meet the limits imposed on automotive emissions, engine control systems are required to constrain air/fuel ratio (AFR) in a narrow band around the stoichiometric value, due to the strong decay of catalyst efficiency in case of rich or lean mixture. This paper presents a model of a sample spark ignition engine and demonstrates Simulink-s capabilities to model an internal combustion engine from the throttle to the crankshaft output. We used welldefined physical principles supplemented, where appropriate, with empirical relationships that describe the system-s dynamic behavior without introducing unnecessary complexity. We also presents a PID tuning method that uses an adaptive fuzzy system to model the relationship between the controller gains and the target output response, with the response specification set by desired percent overshoot and settling time. The adaptive fuzzy based input-output model is then used to tune on-line the PID gains for different response specifications. Experimental results demonstrate that better performance can be achieved with adaptive fuzzy tuning relative to similar alternative control strategies. The actual response specifications with adaptive fuzzy matched the desired response specifications.

Keywords: Modelling, Air–fuel ratio control, SI engine, Adaptive fuzzy Control.

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Authors: Lianglin Xiong, Shouming Zhong, Mao Ye

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This paper considers the robust exponential stability issues for a class of uncertain switched neutral system which delays switched according to the switching rule. The system under consideration includes both stable and unstable subsystems. The uncertainties considered in this paper are norm bounded, and possibly time varying. Based on multiple Lyapunov functional approach and dwell-time technique, the time-dependent switching rule is designed depend on the so-called average dwell time of stable subsystems as well as the ratio of the total activation time of stable subsystems and unstable subsystems. It is shown that by suitably controlling the switching between the stable and unstable modes, the robust stabilization of the switched uncertain neutral systems can be achieved. Two simulation examples are given to demonstrate the effectiveness of the proposed method.

Keywords: Switched neutral system, exponential stability, multiple Lyapunov functional, dwell time technique, time-dependent switching rule.

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Authors: K. P. Oyeduntan, K. Oshinubi

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Nigeria is referred as the ‘Giant of Africa’ due to high population, land mass and large economy. However, it still trails far behind many smaller economies in the continent in terms of maritime operations. As we have seen that the maritime industry is the sparkplug for national growth, because it houses the most crucial infrastructure that generates wealth for a nation, it is worrisome that a nation with six seaports lag in maritime activities. In this research, we have studied how the Gross Domestic Product (GDP) of the maritime transport influences the Nigerian economy. To do this, we applied Simple Linear Regression (SLR), Support Vector Machine (SVM), Polynomial Regression Model (PRM), Generalized Additive Model (GAM) and Generalized Linear Mixed Model (GLMM) to model the relationship between the nation’s Total GDP (TGDP) and the Maritime Transport GDP (MGDP) using a time series data of 20 years. The result showed that the MGDP is statistically significant to the Nigerian economy. Amongst the statistical tool applied, the PRM of order 4 describes the relationship better when compared to other methods. The recommendations presented in this study will guide policy makers and help improve the economy of Nigeria.

Keywords: Economy, GDP, maritime transport, port, regression.

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the  prediction of monthly average daily global solar radiation on  horizontal using recurrent neural networks (RNNs). Climatological  data and measures, mainly air temperature, humidity, sunshine  duration, and wind speed between 1995 and 2007 were used to design  and validate a feed forward and recurrent neural network based  prediction systems. In this paper we present our reference system  based on a feed-forward multilayer perceptron (MLP) as well as the  proposed approach based on an RNN model. The obtained results  were promising and comparable to those obtained by other existing  empirical and neural models. The experimental results showed the  advantage of RNNs over simple MLPs when we deal with time series  solar radiation predictions based on daily climatological data.

Keywords: Recurrent Neural Networks, Global Solar Radiation, Multi-layer perceptron, gradient, Root Mean Square Error.

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Authors: Shivakumar Krishnamurti, Ruchi Agarwal

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The study examines the influence of marital status on consumers of products and services using blogs as a source of information. A pre-designed questionnaire was used to collect the primary data from the respondents (experiences). Data were collected from one hundred and eighty seven respondents residing in and around the Emirates of Sharjah and Dubai of the United Arab Emirates. The collected data was analyzed with the help of statistical tools such as averages, percentages, factor analysis, Student’s t-test and Structural Equation Modelling Technique. Objectives of the study are to know the reasons how married and unmarried or single consumers of products and services are motivated to use blogs as a source of information, to know whether the consumers of products and services irrespective of their marital status share their views and experiences with other bloggers and to know the respondents’ future intentions towards blogging. The study revealed the following: Majority of the respondents have the motivation to blog because they are willing to receive comments on what they post about services, convenience of blogs to search for information about services and products, by blogging respondents share information on the symptoms of a disease/ disorder that may be experienced by someone, helps to share information about ready to cook mix products and are keen to spend more time blogging in the future.

Keywords: Blog, consumer, information, marital status.

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Authors: Emad Amar, Tawfik Khattab, Fatma Zada

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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information about Earthquake Existed throughout history & the Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of the object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, Prediction, RBF neural network.

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Authors: M. Inmaculada Alvarez-Fernández, Celestino González-Nicieza, M. Belén Prendes-Gero, Fernando López-Gayarre

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Among many factors affecting the stability of mining excavations, rock-bursts and tremors play a special role. These dynamic loads occur practically always and have different sources of generation. The most important of them is the commonly used mining technique, which disintegrates a certain area of the rock mass not only in the area of the planned mining, but also creates waves that significantly exceed this area affecting the structural elements. In this work it is analysed the consequences of dynamic loads over the structural elements in an underground room and pillar mine to avoid roof instabilities. With this end, dynamic loads were evaluated through in situ and laboratory tests and simulated with numerical modelling. Initially, the geotechnical characterization of all materials was carried out by mean of large-scale tests. Then, drill holes were done on the roof of the mine and were monitored to determine possible discontinuities in it. Three seismic stations and a triaxial accelerometer were employed to measure the vibrations from blasting tests, establish the dynamic behaviour of roof and pillars and develop the transmission laws. At last, computer simulations by FLAC3D software were done to check the effect of vibrations on the stability of the roofs. The study shows that in-situ tests have a greater reliability than laboratory samples because of eliminating the effect of heterogeneities, that the pillars work decreasing the amplitude of the vibration around them, and that the tensile strength of a beam and depending on its span is overcome with waves in phase and delayed. The obtained transmission law allows designing a blasting which guarantees safety and prevents the risk of future failures.

Keywords: Dynamic modelling, long term instability risks, room and pillar, seismic collapse.

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Authors: Ting (Grace) Lin, Jianhong (Cecilia) Xia, Todd Robinson

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Accessibility analysis, examining people’s ability to access facilities and destinations, is a fundamental assessment for transport planning, policy making, and social exclusion research. Dynamic accessibility which measures accessibility in real-time traffic environment has been an advanced accessibility indicator in transport research. It is also a useful indicator to help travelers to understand travel time daily variability, assists traffic engineers to monitor traffic congestions, and finally develop effective strategies in order to mitigate traffic congestions. This research involved real-time traffic information by collecting travel time data with 15-minute interval via the TomTom^® API. A framework for measuring dynamic accessibility was then developed based on the gravity theory and accessibility dichotomy theory through space and time interpolation. Finally, the dynamic accessibility can be derived at any given time and location under dynamic accessibility spatial analysis framework.

Keywords: Dynamic accessibility, space-time continuum, transport research, TomTom® API.

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Authors: Xinhui Wang, Xiuyong Ding

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This paper addresses the controller synthesis problem of discrete-time switched positive systems with bounded time-varying delays. Based on the switched copositive Lyapunov function approach, some necessary and sufficient conditions for the existence of state-feedback controller are presented as a set of linear programming and linear matrix inequality problems, hence easy to be verified. Another advantage is that the state-feedback law is independent on time-varying delays and initial conditions. A numerical example is provided to illustrate the effectiveness and feasibility of the developed controller.

Keywords: Switched copositive Lyapunov functions, positive linear systems, switched systems, time-varying delays, stabilization.

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Authors: Mengzhuo Luo, Shouming Zhong

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This paper investigates the problem of exponential stability for a class of uncertain discrete-time stochastic neural network with time-varying delays. By constructing a suitable Lyapunov-Krasovskii functional, combining the stochastic stability theory, the free-weighting matrix method, a delay-dependent exponential stability criteria is obtained in term of LMIs. Compared with some previous results, the new conditions obtain in this paper are less conservative. Finally, two numerical examples are exploited to show the usefulness of the results derived.

Keywords: Delay-dependent stability, Neural networks, Time varying delay, Linear matrix inequality (LMI).

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Authors: Yingguo Li

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In this paper, we consider a discrete Gompertz model with time delay. Firstly, the stability of the equilibrium of the system is investigated by analyzing the characteristic equation. By choosing the time delay as a bifurcation parameter, we prove that Neimark- Sacker bifurcations occur when the delay passes a sequence of critical values. The direction and stability of the Neimark-Sacker are determined by using normal forms and centre manifold theory. Finally, some numerical simulations are given to verify the theoretical analysis.

Keywords: Gompertz system, Neimark-Sacker bifurcation, stability, time delay.

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Authors: Jin A Ryu, Ga Ye Kim, Hee Sun Kim

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As the number of fire accidents is gradually raising, many studies have been reported on evacuation. Previous studies have mostly focused on evaluating the safety of evacuation and the risk of fire in particular buildings. However, studies on effects of various parameters on evacuation have not been nearly done. Therefore, this paper aims at observing evacuation time under the effect of fire initiated location. In this study, evacuation simulations are performed on a 5-floor building located in Seoul, South Korea using the commercial program, Fire Dynamics Simulator with Evacuation (FDS+EVAC). Only the fourth and fifth floors are modeled with an assumption that fire starts in a room located on the fourth floor. The parameter for evacuation simulations is location of fire initiation to observe the evacuation time and safety. Results show that the location of fire initiation is closer to exit, the more time is taken to evacuate. The case having the nearest location of fire initiation to exit has the lowest ratio of successful occupants to the total occupants. In addition, for safety evaluation, the evacuation time calculated from computer simulation model is compared with the tolerable evacuation time according to code in Japan. As a result, all cases are completed within the tolerable evacuation time. This study allows predicting evacuation time under various conditions of fire and can be used to evaluate evacuation appropriateness and fire safety of building.

Keywords: Evacuation safety, Evacuation simulation, FDS+Evac, Time.

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Authors: E. Menga, S. Hernandez

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Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: Frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber.

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Authors: Liyakathunisa, V. K. Ananthashayana

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Crucial information barely visible to the human eye is often embedded in a series of low resolution images taken of the same scene. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. The ideal algorithm should be fast, and should add sharpness and details, both at edges and in regions without adding artifacts. In this paper we propose a super resolution blind reconstruction technique for linearly degraded images. In our proposed technique the algorithm is divided into three parts an image registration, wavelets based fusion and an image restoration. In this paper three low resolution images are considered which may sub pixels shifted, rotated, blurred or noisy, the sub pixel shifted images are registered using affine transformation model; A wavelet based fusion is performed and the noise is removed using soft thresolding. Our proposed technique reduces blocking artifacts and also smoothens the edges and it is also able to restore high frequency details in an image. Our technique is efficient and computationally fast having clear perspective of real time implementation.

Keywords: Affine Transforms, Denoiseing, DWT, Fusion, Image registration.

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Authors: Sahar Sohrabi

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The emergence of Cloud data centers has revolutionized the IT industry. Private Clouds in specific provide Cloud services for certain group of customers/businesses. In a real-time private Cloud each task that is given to the system has a deadline that desirably should not be violated. Scheduling tasks in a real-time private CLoud determine the way available resources in the system are shared among incoming tasks. The aim of the scheduling policy is to optimize the system outcome which for a real-time private Cloud can include: energy consumption, deadline violation, execution time and the number of host switches. Different scheduling policies can be used for scheduling. Each lead to a sub-optimal outcome in a certain settings of the system. A Bayesian Scheduling strategy is proposed for scheduling to further improve the system outcome. The Bayesian strategy showed to outperform all selected policies. It also has the flexibility in dealing with complex pattern of incoming task and has the ability to adapt.

Keywords: Bayesian, cloud computing, real-time private cloud, scheduling.

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Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

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Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: Foreign Direct Investments, methods, statistics, analysis.

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Authors: Irena Palić

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The main objective of the research in this paper is to empirically assess the causal relationship of private savings and economic growth in the Republic of Croatia. Households’ savings are approximated by household deposits in banks, while domestic income is approximated by industrial production volume indices. Vector Autoregression model and Granger causality tests are used to in order to analyse the relationship among private savings and economic growth. Since ADF unit root tests have shown that both mentioned series are non stationary at levels, series are first differenced in order to become stationary. Therefore, VAR model is estimated with percentage change in private savings and percentage change in domestic income, which can be interpreted as economic growth in case of positive percentage change in domestic income. The Granger causality test has shown that there is no causal relationship among private savings and economic growth in Croatia. The impulse response functions have shown that the impact of shock in domestic income on private savings change is stronger than the impact of private saving on growth. Variance decompositions show that both economic growth and private saving change explain the largest part of its own forecast variance. The research has shown that the link between private savings economic and growth in Croatia is weak, what is in line with relevant empirical research in small open economies.

Keywords: Economic growth, Granger causality, innovation analysis, private savings, Vector Autoregression model.

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Authors: Eleni Giouli

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Distance learning provides a flexible approach to education, enabling busy learners to complete their coursework at their own pace, on their own schedule, and from a convenient location. This flexibility combined with a series of other issues; make the benefits of lifelong distance learning numerous. The purpose of the paper is to investigate whether distance education can contribute to the improvement of adult skills in Greece, highlighting in this way the necessity of the lifelong distance learning. To investigate this goal, a questionnaire is constructed and analyzed based on responses from 3,016 attendees of lifelong distance learning programs in the e-learning of the National and Kapodistrian University of Athens in Greece. In order to do so, a series of relationships is examined including the effects of a) the gender, b) the previous educational level, c) the current employment status, and d) the method used in the distance learning program, on the development of new general, technical, administrative, social, cultural, entrepreneurial and green skills. The basic conclusions that emerge after using a binary logistic framework are that the following factors are critical in order to develop new skills: the gender, the education level and the educational method used in the lifelong distance learning program. The skills more significantly affected by those factors are the acquiring new skills in general, as well as acquiring general, language and cultural, entrepreneurial and green skills, while for technical and social skills only gender and educational method play a crucial role. Moreover, routine skills and social skills are not affected by the four factors included in the analysis.

Keywords: Adult skills, distance learning, education, lifelong learning.

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Authors: Ali Nadi, Ali Edrissi

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Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: Disaster management, real-time demand, reinforcement learning, relief demand.

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Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell

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Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.

Keywords: CHPV, thermal storage, control, dynamic simulation.

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Authors: M. Zahid Hossain, M. Ashraful Amin

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The algorithms of convex hull have been extensively studied in literature, principally because of their wide range of applications in different areas. This article presents an efficient algorithm to construct approximate convex hull from a set of n points in the plane in O(n + k) time, where k is the approximation error control parameter. The proposed algorithm is suitable for applications preferred to reduce the computation time in exchange of accuracy level such as animation and interaction in computer graphics where rapid and real-time graphics rendering is indispensable.

Keywords: Convex hull, Approximation algorithm, Computational geometry, Linear time.

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Authors: Haoyu Ma, Bin Hu, Mike Jackson, Jingzhi Yan, Wen Zhao

Abstract:

In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Keywords: Sleep, Sleep stage, Automatic sleep scoring, Electroencephalography, Decision tree, Artificial neural network

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