Search results for: Dynamic analyze

Authors: L. Mahdavian, M. Raouf

Abstract:

Three dimensional nanostructure materials have attracted the attention of many researches because the possibility to apply them for near future devices in sensors, catalysis and energy related. Tin dioxide is the most used material for gas sensing because its three-dimensional nanostructures and properties are related to the large surface exposed to gas adsorption. We propose the use of branch SnO2 nanowhiskers in interaction with ethanol. All Sn atoms are symmetric. The total energy, potential energy and Kinetic energy calculated for interaction between SnO2 and ethanol in different distances and temperatures. The calculations achieved by methods of Langevin Dynamic and Mont Carlo simulation. The total energy increased with addition ethanol molecules and temperature so interactions between them are endothermic.

Keywords: Tin dioxide, nanowhisker, Ethanol, Langevin Dynamic and Mont Carlo Simulation.

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Authors: R. Mangiaracina, A. Perego, F. Campari

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Despite the fact that B2c eCommerce has become important in numerous economies, its adoption varies from country to country. This paper aims to identify the factors affecting (enabling or inhibiting) B2c eCommerce and to determine their quantitative impact on the diffusion of online sales across countries. A dynamic panel model analyzing the relationship between 13 factors (Macroeconomic, Demographic, Socio-Cultural, Infrastructural and Offer related) stemming from a complete literature analysis and the B2c eCommerce value in 45 countries over 9 years has been developed. Having a positive correlation coefficient, GDP, mobile penetration, Internet user penetration and credit card penetration resulted as enabling drivers of the B2c eCommerce value across countries, whereas, having a negative correlation coefficient,equal distribution of income and the development of traditional retailing network act as inhibiting factors.

Keywords: B2c eCommerce diffusion, influencing factors, dynamic panel model

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Authors: A. R. Tavakolpour-Saleh, A. R. Setoodeh, E. Ansari

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This paper presents modeling and control of a highly nonlinear system including, non-interacting two spherical tanks using iterative learning control (ILC). Consequently, the objective of the paper is to control the liquid levels in the nonlinear tanks. First, a proportional-integral-derivative (PID) controller is applied to the plant model as a suitable benchmark for comparison. Then, dynamic responses of the control system corresponding to different step inputs are investigated. It is found that the conventional PID control is not able to fulfill the design criteria such as desired time constant. Consequently, an iterative learning controller is proposed to accurately control the coupled nonlinear tanks system. The simulation results clearly demonstrate the superiority of the presented ILC approach over the conventional PID controller to cope with the nonlinearities presented in the dynamic system.

Keywords: Iterative learning control, spherical tanks, nonlinear system.

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Authors: J. Ritonja, B. Grcar

Abstract:

For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: Eigenvalue analysis, mathematical model, power system stability, synchronous generator.

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Authors: Laidson P. Gomes, Cristina T. Andrade, Eduardo M. Del Aguila, Cameron Alexander, Vânia M. F. Paschoalin

Abstract:

Chitosan is a natural polysaccharide prepared by the N-deacetylation of chitin. In this study, the physicochemical and antibacterial properties of chitosan nanoparticles, produced by ultrasound irradiation, were evaluated. The physicochemical properties of the nanoparticles were determined by dynamic light scattering and zeta potential analysis. Chitosan nanoparticles inhibited the growth of E. coli. The minimum inhibitory concentration (MIC) values were lower than 0.5 mg/mL, and the minimum bactericidal concentration (MBC) values were similar or higher than MIC values. Confocal laser scanning micrographs (CLSM) were used to observe the interaction between E. coli suspensions mixed with FITC-labeled chitosan polymers and nanoparticles.

Keywords: Chitosan nanoparticles, dynamic light scattering, zeta potential, confocal microscopy, antibacterial activity.

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Authors: Cauvery N. K., K. V. Viswanatha

Abstract:

Mobile Ad hoc network consists of a set of mobile nodes. It is a dynamic network which does not have fixed topology. This network does not have any infrastructure or central administration, hence it is called infrastructure-less network. The change in topology makes the route from source to destination as dynamic fixed and changes with respect to time. The nature of network requires the algorithm to perform route discovery, maintain route and detect failure along the path between two nodes [1]. This paper presents the enhancements of ARA [2] to improve the performance of routing algorithm. ARA [2] finds route between nodes in mobile ad-hoc network. The algorithm is on-demand source initiated routing algorithm. This is based on the principles of swarm intelligence. The algorithm is adaptive, scalable and favors load balancing. The improvements suggested in this paper are handling of loss ants and resource reservation.

Keywords: Ad hoc networks, On-demand routing, Swarmintelligence.

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Authors: Walid MOUDANI

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.

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Authors: Toi Limazie, Xun'an Zhang, Xianjie Wang

Abstract:

This paper focuses on the Mega-Sub Controlled Structure Systems (MSCSS) performances and characteristics regarding the new control principle contained in MSCSS subjected to strong earthquake excitations. The adopted control scheme consists of modulated sub-structures where the control action is achieved by viscous dampers and sub-structure own configuration. The elastic-plastic time history analysis under severe earthquake excitation is analyzed base on the Finite Element Analysis Method (FEAM), and some comparison results are also given in this paper. The result shows that the MSCSS systems can remarkably reduce vibrations effects more than the mega-sub structure (MSS). The study illustrates that the improved MSCSS presents good seismic resistance ability even at 1.2g and can absorb seismic energy in the structure, thus imply that structural members cross section can be reduce and achieve to good economic characteristics. Furthermore, the elasto-plastic analysis demonstrates that the MSCSS is accurate enough regarding international building evaluation and design codes. This paper also shows that the elasto-plastic dynamic analysis method is a reasonable and reliable analysis method for structures subjected to strong earthquake excitations and that the computed results are more precise.

Keywords: controlling effectiveness, Elasto-plastic dynamic analysis, Mega-Sub Controlled Structure, Plastic hinge pattern.

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Authors: Shobha Sharma, Amita Dev

Abstract:

This research paper presents highly optimized barrel shifter at 22nm Hi K metal gate strained Si technology node. This barrel shifter is having a unique combination of static and dynamic body bias which gives lowest power delay product. This power delay product is compared with the same circuit at same technology node with static forward biasing at ‘supply/2’ and also with normal reverse substrate biasing and still found to be the lowest. The power delay product of this barrel sifter is .39362X10-17J and is lowered by approximately 78% to reference proposed barrel shifter at 32nm bulk CMOS technology. Power delay product of barrel shifter at 22nm Hi K Metal gate technology with normal reverse substrate bias is 2.97186933X10-17J and can be compared with this design’s PDP of .39362X10-17J. This design uses both static and dynamic substrate biasing and also has approximately 96% lower power delay product compared to only forward body biased at half of supply voltage. The NMOS model used are predictive technology models of Arizona state university and the simulations to be carried out using HSPICE simulator.

Keywords: Dynamic body biasing, highly optimized barrel shifter, PDP, Static body biasing.

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Authors: Alexandra Aslanidou

Abstract:

The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: General data protection regulation, human resource management, educational system.

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Authors: Hamed Sabahno

Abstract:

In this paper, an inventory model with finite and constant replenishment rate, price dependant demand rate, time value of money and inflation, finite time horizon, lead time and exponential deterioration rate and with the objective of maximizing the present worth of the total system profit is developed. Using a dynamic programming based solution algorithm, the optimal sequence of the cycles can be found and also different optimal selling prices, optimal order quantities and optimal maximum inventories can be obtained for the cycles with unequal lengths, which have never been done before for this model. Also, a numerical example is used to show accuracy of the solution procedure.

Keywords: Deteriorating items, Dynamic programming, Finitereplenishment rate, Inventory control, Operation Research.

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Authors: Phu-Cuong Nguyen, Seung-Eock Kim

Abstract:

This paper presents nonlinear elastic dynamic analysis of 3-D semi-rigid steel frames including geometric and connection nonlinearities. The geometric nonlinearity is considered by using stability functions and updating geometric stiffness matrix. The nonlinear behavior of the steel beam-to-column connection is considered by using a zero-length independent connection element comprising of six translational and rotational springs. The nonlinear dynamic equilibrium equations are solved by the Newmark numerical integration method. The nonlinear time-history analysis results are compared with those of previous studies and commercial SAP2000 software to verify the accuracy and efficiency of the proposed procedure.

Keywords: Geometric nonlinearity, nonlinear time-historyanalysis, semi-rigid connection, stability functions.

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Authors: Y. S. Tai, M. Y. Huang, H. T. Hu

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The commercial finite element program LS-DYNA was employed to evaluate the response and energy absorbing capacity of cylindrical metal tubes that are externally wrapped with composite. The effects of composite wall thickness, loading conditions and fiber ply orientation were examined. The results demonstrate that a wrapped composite can be utilized effectively to enhance the crushing characteristics and energy absorbing capacity of the tubes. Increasing the thickness of the composite increases the mean force and the specific energy absorption under both static and dynamic crushing. The ply pattern affects the energy absorption capacity and the failure mode of the metal tube and the composite material property is also significant in determining energy absorption efficiency.

Keywords: fiber-reinforced metal tubes, energy absorption, axial crushing, impact loading.

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Authors: Banaja Mohanty, Prakash Kumar Hota

Abstract:

This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.

Keywords: Automatic generation control, governor dead band, generation rate constraint, differential evolution.

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Authors: Kaan T. Oner, Ertugrul Cetinsoy, Efe Sirimoglu, Cevdet Hancer, Taylan Ayken, Mustafa Unel

Abstract:

We present our ongoing work on the development of a new quadrotor aerial vehicle which has a tilt-wing mechanism. The vehicle is capable of take-off/landing in vertical flight mode (VTOL) and flying over long distances in horizontal flight mode. Full dynamic model of the vehicle is derived using Newton-Euler formulation. Linear and nonlinear controllers for the stabilization of attitude of the vehicle and control of its altitude have been designed and implemented via simulations. In particular, an LQR controller has been shown to be quite effective in the vertical flight mode for all possible yaw angles. A sliding mode controller (SMC) with recursive nature has also been proposed to stabilize the vehicle-s attitude and altitude. Simulation results show that proposed controllers provide satisfactory performance in achieving desired maneuvers.

Keywords: UAV, VTOL, dynamic model, stabilization, LQR, SMC

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Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin

Abstract:

MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.

Keywords: Computer Vision, MediaPipe, Adaptive Boosting, Fast Dynamic Time Warping.

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Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

Abstract:

In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: Growth management, land use externalities, land value, spatial panel dynamic.

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Authors: Nikunj Agarwal, M. P. Sebastian

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Cloud computing can reduce the start-up expenses of implementing EHR (Electronic Health Records). However, many of the healthcare institutions are yet to implement cloud computing due to the associated privacy and security issues. In this paper, we analyze the challenges and opportunities of implementing cloud computing in healthcare. We also analyze data of over 5000 US hospitals that use Telemedicine applications. This analysis helps to understand the importance of smart phones over the desktop systems in different departments of the healthcare institutions. The wide usage of smartphones and cloud computing allows ubiquitous and affordable access to the health data by authorized persons, including patients and doctors. Cloud computing will prove to be beneficial to a majority of the departments in healthcare. Through this analysis, we attempt to understand the different healthcare departments that may benefit significantly from the implementation of cloud computing.

Keywords: Cloud computing, smart devices, healthcare, telemedicine.

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Authors: Rawaa H. El-Bidweihy, Hisham M. Abdelsalam, Ihab A. El-Khodary

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Bayesian networks are now considered to be a promising tool in the field of energy with different applications. In this study, the aim was to indicate the states of a previous constructed Bayesian network related to the solar energy in Egypt and the factors affecting its market share, depending on the followed data distribution type for each factor, and using either the Z-distribution approach or the Chebyshev’s inequality theorem. Later on, the separate and the conditional probabilities of the states of each factor in the Bayesian network were derived, either from the collected and scrapped historical data or from estimations and past studies. Results showed that we could use the constructed model for scenario and decision analysis concerning forecasting the total percentage of the market share of the solar energy in Egypt by 2035 and using it as a stable renewable source for generating any type of energy needed. Also, it proved that whenever the use of the solar energy increases, the total costs decreases. Furthermore, we have identified different scenarios, such as the best, worst, 50/50, and most likely one, in terms of the expected changes in the percentage of the solar energy market share. The best scenario showed an 85% probability that the market share of the solar energy in Egypt will exceed 10% of the total energy market, while the worst scenario showed only a 24% probability that the market share of the solar energy in Egypt will exceed 10% of the total energy market. Furthermore, we applied policy analysis to check the effect of changing the controllable (decision) variable’s states acting as different scenarios, to show how it would affect the target nodes in the model. Additionally, the best environmental and economical scenarios were developed to show how other factors are expected to be, in order to affect the model positively. Additional evidence and derived probabilities were added for the weather dynamic nodes whose states depend on time, during the process of converting the Bayesian network into a dynamic Bayesian network.

Keywords: Bayesian network, Chebyshev, decision variable, dynamic Bayesian network, Z-distribution

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Authors: Yufu Yin, Tao Lin, Shanghong Zhao, Zihang Zhu, Xuan Li, Wei Jiang, Qiurong Zheng, Hui Wang

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In this paper, a frequency-dependent and tunable phase shifter is proposed and numerically analyzed. The key devices are the dual-polarization binary phase shift keying modulator (DP-BPSK) and the fiber Bragg grating (FBG). The phase-frequency response of the FBG is employed to determine the frequency-dependent phase shift. The simulation results show that a linear phase shift of the recovered output microwave signal which depends on the frequency of the input RF signal is achieved. In addition, by adjusting the power of the RF signal, the full range phase shift from 0° to 360° can be realized. This structure shows the spurious free dynamic range (SFDR) of 70.90 dB·Hz^2/3 and 72.11 dB·Hz^2/3 under different RF powers.

Keywords: Microwave photonics, phase shifter, spurious free dynamic range, frequency-dependent.

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Authors: Ivan Yatchev, Ewen Ritchie

Abstract:

Comparison of two approaches for the simulation of the dynamic behaviour of a permanent magnet linear actuator is presented. These are full coupled model, where the electromagnetic field, electric circuit and mechanical motion problems are solved simultaneously, and decoupled model, where first a set of static magnetic filed analysis is carried out and then the electric circuit and mechanical motion equations are solved employing bi-cubic spline approximations of the field analysis results. The results show that the proposed decoupled model is of satisfactory accuracy and gives more flexibility when the actuator response is required to be estimated for different external conditions, e.g. external circuit parameters or mechanical loads.

Keywords: Coupled problems, dynamic models, finite elementanalysis, linear actuators, permanent magnets.

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Authors: Akram Hatami, Naser Firoozi, Vesa Puhakka

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Ethics and responsibility are rapidly becoming a distinguishing feature of organizations. In this paper, we analyze ethics and responsibility in shadow factories in China. We engage ourselves with Bauman’s moral impulse perspective because his idea can contextualize ethics and responsibility. Moral impulse is a feeling of a selfless, infinite and unconditional responsibility towards, and care for, Others. We analyze a case study from a secondary data source because, for such a critical phenomenon as business ethics in shadow factories, collecting primary data is difficult, since they are unregistered factories. We argue that there has not been enough attention given to the ethics and responsibility in shadow factories in China. Our main goal is to demonstrate that, considering the Other, more importantly the employees, in ethical decision-making is a simple instruction beyond the narrow version of ethics by ethical codes and rules.

Keywords: Moral impulse, responsibility, shadow factories, the other.

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Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

Abstract:

The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, Dynamic Programming, Monte Carlo simulation, Periodic replacement, Weibull distribution.

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Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: Differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control.

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Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: Behavior, big data, hierarchical Hidden Markov Model, intelligent object.

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Authors: Kayijuka Idrissa

Abstract:

This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: Statistical methods, Poisson distribution, car moving techniques, traffic flow.

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Authors: Sara Felloni, Giuliano Strini

Abstract:

We explore entanglement in composite quantum systems and how its peculiar properties are exploited in quantum information and communication protocols by means of Diagrams of States, a novel method to graphically represent and analyze how quantum information is elaborated during computations performed by quantum circuits. We present quantum diagrams of states for Bell states generation, measurements and projections, for dense coding and quantum teleportation, for probabilistic quantum machines designed to perform approximate quantum cloning and universal NOT and, finally, for quantum privacy amplification based on entanglement purification. Diagrams of states prove to be a useful approach to analyze quantum computations, by offering an intuitive graphic representation of the processing of quantum information. They also help in conceiving novel quantum computations, from describing the desired information processing to deriving the final implementation by quantum gate arrays.

Keywords: Diagrams of states, entanglement, quantum circuits, quantum information.

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Authors: D. Sumathi, P. Poongodi

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Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.

Keywords: Software as a Service (SaaS), Trust, Heterogeneous Earliest Finish Time (HEFT) algorithm, Dynamic Load Scheduling.

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Authors: Sima Sh. Alian, Abdul Aziz Omar, Ali F. Alta'ee, Irzie Hani

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In this work, the precipitation of asphaltene from a Malaysian light oil reservoir was studies. A series of experiments were designed and carried out to examine the effect of CO2 injection on asphaltene precipitation. Different pressures of injections were used in Dynamic flooding experiment in order to investigate the effect of pressure versus injection pore volume of CO2. These dynamic displacement tests simulate reservoir condition. Results show that by increasing the pore volume of injected gas asphaltene precipitation will increases, also rise in injection pressure causes less precipitation. Sandstone core plug was used to represent reservoir formation during displacement test; therefore it made it possible to study the effect of present of asphaltene on formation. It is found out that the precipitated asphaltene can reduce permeability and porosity which is not favorable during oil production.

Keywords: Asphaltene, asphaltene precipitation, enhanced oil recovery.

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Authors: Sudhir Jagtap, Kodge B. G., Shinde G. N., Devshette P. M

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Numerical analysis naturally finds applications in all fields of engineering and the physical sciences, but in the 21st century, the life sciences and even the arts have adopted elements of scientific computations. The numerical data analysis became key process in research and development of all the fields [6]. In this paper we have made an attempt to analyze the specified numerical patterns with reference to the association rule mining techniques with minimum confidence and minimum support mining criteria. The extracted rules and analyzed results are graphically demonstrated. Association rules are a simple but very useful form of data mining that describe the probabilistic co-occurrence of certain events within a database [7]. They were originally designed to analyze market-basket data, in which the likelihood of items being purchased together within the same transactions are analyzed.

Keywords: Numerical data analysis, Data Mining, Association Rule Mining

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