Search results for: Multivariate time series

Authors: Shan Gao

Abstract:

This paper treats a discrete-time finite buffer batch arrival queue with a single working vacation and partial batch rejection in which the inter-arrival and service times are, respectively, arbitrary and geometrically distributed. The queue is analyzed by using the supplementary variable and the imbedded Markov-chain techniques. We obtain steady-state system length distributions at prearrival, arbitrary and outside observer-s observation epochs. We also present probability generation function (p.g.f.) of actual waiting-time distribution in the system and some performance measures.

Keywords: Discrete-time, finite buffer, single working vacation, batch arrival, partial rejection.

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Authors: Joe Imae, Kenjiro Shinagawa, Tomoaki Kobayashi, Guisheng Zhai

Abstract:

We propose a new approach on how to obtain the approximate solutions of Hamilton-Jacobi (HJ) equations. The process of the approximation consists of two steps. The first step is to transform the HJ equations into the virtual time based HJ equations (VT-HJ) by introducing a new idea of ‘virtual-time’. The second step is to construct the approximate solutions of the HJ equations through a computationally iterative procedure based on the VT-HJ equations. It should be noted that the approximate feedback solutions evolve by themselves as the virtual-time goes by. Finally, we demonstrate the effectiveness of our approximation approach by means of simulations with linear and nonlinear control problems.

Keywords: Nonlinear Control, Optimal Control, Hamilton-Jacobi Equation, Virtual-Time

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Authors: M. Y. Lee, D. H. Shin, S. H. Park, W.C. Ham, S.K. Ko, C. G. Song

Abstract:

Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Keywords: Photoacoustic tomography, inflammation detection, rat, kidney, contrast agent, ultrasound.

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Authors: Shinpei Kato, Nobuyuki Yamasaki

Abstract:

This paper proposes a scheduling scheme using feedback control to reduce the response time of aperiodic tasks with soft real-time constraints. We design an algorithm based on the proposed scheduling scheme and Total Bandwidth Server (TBS) that is a conventional server technique for scheduling aperiodic tasks. We then describe the feedback controller of the algorithm and give the control parameter tuning methods. The simulation study demonstrates that the algorithm can reduce the mean response time up to 26% compared to TBS in exchange for slight deadline misses.

Keywords: Real-Time Systems, Aperiodic Task Scheduling, Feedback-Control Scheduling, Total Bandwidth Server.

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Authors: Kemalettin Erbatur, Özer Koca, Evrim Taşkıran, Metin Yılmaz, Utku Seven

Abstract:

Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots. However, the walking control for bipedal robots is a challenging task due to their complex dynamics. Stable reference generation plays a very important role in control. Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable walking reference generation of biped walking robots. This paper follows this main approach too. We propose a natural and continuous ZMP reference trajectory for a stable and human-like walk. The ZMP reference trajectories move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained from predefined ZMP reference trajectories by a Fourier series approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference trajectories possess pre-assigned single and double support phases, which are very useful in experimental tuning work. The ZMP based reference generation strategy is tested via threedimensional full-dynamics simulations of a 12-degrees-of-freedom biped robot model. Simulation results indicate that the proposed reference trajectory generation technique is successful.

Keywords: Biped robot, Linear Inverted Pendulum Model, Zero Moment Point, Fourier series approximation.

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Authors: A. M. Azad, M. Alam, C. M. Hussain

Abstract:

In this paper, we have presented the effect of varying time-delays on performance and stability in the single-channel multirate sampled-data system in hard real-time (RT-Linux) environment. The sampling task require response time that might exceed the capacity of RT-Linux. So a straight implementation with RT-Linux is not feasible, because of the latency of the systems and hence, sampling period should be less to handle this task. The best sampling rate is chosen for the sampled-data system, which is the slowest rate meets all performance requirements. RT-Linux is consistent with its specifications and the resolution of the real-time is considered 0.01 seconds to achieve an efficient result. The test results of our laboratory experiment shows that the multi-rate control technique in hard real-time operating system (RTOS) can improve the stability problem caused by the random access delays and asynchronization.

Keywords: Multi-rate, PID, RT-Linux, Sampled-data, Servo.

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Authors: Budiyono, I N. Widiasa, S. Johari, Sunarso

Abstract:

In this study, the kinetic of biogas production was studied by performing a series laboratory experiment using rumen fluid of animal ruminant as inoculums. Cattle manure as substrate was inoculated by rumen fluid to the anaerobic biodigester. Laboratory experiments using 400 ml biodigester were performed in batch operation mode. Given 100 grams of fresh cattle manure was fed to each biodigester and mixed with rumen fluid by manure : rumen weight ratio of 1:1 (MR11). The operating temperatures were varied at room temperature and 38.5 oC. The cumulative volume of biogas produced was used to measure the biodigester performance. The research showed that the rumen fluid inoculated to biodigester gave significant effect to biogas production (P<0.05). Rumen fluid inoculums caused biogas production rate and efficiency increase two to three times in compare to manure substrate without rumen fluid. With the rumen fluid inoculums, gave the kinetic parameters of biogas production i.e biogas production rate constants (U), maximum biogas production (A), and minimum time to produce biogas (λ) are 3.89 ml/(gVS.day); 172.51 (ml/gVS); dan 7.25 days, respectively. While the substrate without rumen fluid gave the kinetic parameters U, A, and λ are 1.74 ml/(gVS.day); 73.81 (ml/gVS); dan 14.75 days, respectively. The future work will be carried out to study the dynamics of biogas production if both the rumen inoculums and manure are fed in the continuous system.

Keywords: rumen fluid, inoculums, anaerobic digestion, biogasproduction.

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Authors: G. Gürsel, K. H. Gülkesen, N. Zayim, A. Arifoğlu, O. Saka

Abstract:

User satisfaction is one of the most used success indicators in the research of information system (IS). Literature shows user expectations have great influence on user satisfaction. Both expectation and satisfaction of users are important for Hospital Information Systems (HIS). Education, IS experience, age, attitude towards change, business title, sex and working unit of the hospital, are examined as the potential determinant of the medical users’ expectations. Data about medical user expectations are collected by the “Expectation Questionnaire” developed for this study. Expectation data are used for calculating the Expectation Meeting Ratio (EMR) with the evaluation framework also developed for this study. The internal consistencies of the answers to the questionnaire are measured by Cronbach´s Alpha coefficient. The multivariate analysis of medical user’s EMRs of HIS is performed by forward stepwise binary logistic regression analysis. Education and business title is appeared to be the determinants of expectations from HIS.

Keywords: Evaluation, Fuzzy Logic, Hospital Information System, User Expectation.

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Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Shehzad Ashraf Ch., Aftab Ahmed Khan, Zahid Mehmood, Muhammad Ahsan Habib, Qasim Mehmood

Abstract:

Energy efficiency is the key requirement in wireless sensor network as sensors are small, cheap and are deployed in very large number in a large geographical area, so there is no question of replacing the batteries of the sensors once deployed. Different ways can be used for efficient energy transmission including Multi-Hop algorithms, collaborative communication, cooperativecommunication, Beam- forming, routing algorithm, phase, frequency and time synchronization. The paper reviews the need for time synchronization and proposed a BFS based synchronization algorithm to achieve energy efficiency. The efficiency of our protocol has been tested and verified by simulation

Keywords: time synchronization, sensor networks, energy efficiency, breadth first search

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Authors: Adrian Lo

Abstract:

Since the advent of modern architecture, notions of free plan and transparency have proliferated well into current trends. The movement’s notion of a spatially homogeneous, open and limitless ‘free plan’ contrasts with the spatially heterogeneous ‘series of rooms’ defined by load bearing walls, which in turn triggered new notions of transparency created by vast expanses of glazed walls. Similarly, transparency was also dichotomized as something that was physical or optical, as well as something conceptual, akin to spatial organization. As opposed to merely accepting the duality and possible incompatibility of these dichotomies, this paper seeks to ask how can space be both literally and phenomenally transparent, as well as exhibit both homogeneous and heterogeneous qualities? This paper explores this potential destabilization or blurring of spatial phenomena by dissecting the transparent layers and volumes of a series of selected case studies to investigate how different architects have devised strategies of spatial ambiguity and interpenetration. Projects by Peter Eisenman, Sou Fujimoto, and SANAA will be discussed and analyzed to show how the superimposition of geometries and spaces achieve different conditions of layering, transparency, and interstitiality. Their particular buildings will be explored to reveal various innovative kinds of spatial interpenetration produced through the articulate relations of the elements of architecture, which challenge conventional perceptions of interior and exterior whereby visual homogeneity blurs with spatial heterogeneity. The results show how spatial conceptions such as interpenetration and transparency have the ability to subvert not only inside-outside dialectics, but could also produce multiple degrees of interiority within complex and indeterminate spatial dimensions in constant flux as well as present alternative forms of social interaction.

Keywords: interpenetration, literal and phenomenal transparency, spatial heterogeneity, visual homogeneity

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Authors: Hala Abdel hameed, Hazem M. El-Bakry, Torky Sultan

Abstract:

There are many issues that affect modeling and designing real-time databases. One of those issues is maintaining consistency between the actual state of the real-time object of the external environment and its images as reflected by all its replicas distributed over multiple nodes. The need to improve the scalability is another important issue. In this paper, we present a general framework to design a replicated real-time database for small to medium scale systems and maintain all timing constrains. In order to extend the idea for modeling a large scale database, we present a general outline that consider improving the scalability by using an existing static segmentation algorithm applied on the whole database, with the intent to lower the degree of replication, enables segments to have individual degrees of replication with the purpose of avoiding excessive resource usage, which all together contribute in solving the scalability problem for DRTDBS.

Keywords: Database modeling, Distributed database, Real time databases, Replication

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Authors: Sajad Farokhi, Siti Mariyam Shamsuddin, Jan Flusser, Usman Ullah Sheikh

Abstract:

Although face recognition seems as an easy task for human, automatic face recognition is a much more challenging task due to variations in time, illumination and pose. In this paper, the influence of time-lapse on visible and thermal images is examined. Orthogonal moment invariants are used as a feature extractor to analyze the effect of time-lapse on thermal and visible images and the results are compared with conventional Principal Component Analysis (PCA). A new triangle square ratio criterion is employed instead of Euclidean distance to enhance the performance of nearest neighbor classifier. The results of this study indicate that the ideal feature vectors can be represented with high discrimination power due to the global characteristic of orthogonal moment invariants. Moreover, the effect of time-lapse has been decreasing and enhancing the accuracy of face recognition considerably in comparison with PCA. Furthermore, our experimental results based on moment invariant and triangle square ratio criterion show that the proposed approach achieves on average 13.6% higher in recognition rate than PCA.

Keywords: Infrared Face recognition, Time-lapse, Zernike moment invariants

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: Energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning.

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Authors: R. Afroundeh, T. Arimitsu, R. Yamanaka, C. S. Lian, T. Yunoki, T. Yano, K. Shirakawa

Abstract:

We investigated this hypothesis that arterial CO2 pressure (PaCO2) drives ventilation (V.E) with a time delay duringrecovery from short impulse-like exercise (10 s) with work load of 200 watts. V.E and end tidal CO2 pressure (PETCO2) were measured continuously during rest, warming up, exercise and recovery periods. PaCO2 was predicted (PaCO2 pre) from PETCO2 and tidal volume (VT). PETCO2 and PaCO2 pre peaked at 20 s of recovery. V.E increased and peaked at the end of exercise and then decreased during recovery; however, it peaked again at 30 s of recovery, which was 10 s later than the peak of PaCO2 pre. The relationship between V. E and PaCO2pre was not significant by using data of them obtained at the same time but was significant by using data of V.E obtained 10 s later for data of PaCO2 pre. The results support our hypothesis that PaCO2 drives V.E with a time delay.

Keywords: Arterial CO2 pressure, impulse-like exercise, time delay, ventilation.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: Hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control.

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Authors: Chien-Min Chu, Bor-Wen Tsai, Kang-Tsung Chang

Abstract:

Landslide susceptibility map delineates the potential zones for landslide occurrence. Previous works have applied multivariate methods and neural networks for mapping landslide susceptibility. This study proposed a new approach to integrate decision tree model and spatial cluster statistic for assessing landslide susceptibility spatially. A total of 2057 landslide cells were digitized for developing the landslide decision tree model. The relationships of landslides and instability factors were explicitly represented by using tree graphs in the model. The local Getis-Ord statistics were used to cluster cells with high landslide probability. The analytic result from the local Getis-Ord statistics was classed to create a map of landslide susceptibility zones. The map was validated using new landslide data with 482 cells. Results of validation show an accuracy rate of 86.1% in predicting new landslide occurrence. This indicates that the proposed approach is useful for improving landslide susceptibility mapping.

Keywords: Landslide susceptibility Zonation, Decision treemodel, Spatial cluster, Local Getis-Ord statistics.

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Authors: M. Duran Toksarı, B. Uçarkuş

Abstract:

In this paper, we propose two algorithms to optimally solve makespan and total completion time scheduling problems with learning effect and job dependent delivery times in a single machine environment. The delivery time is the extra time to eliminate adverse effect between the main processing and delivery to the customer. In this paper, we introduce the job dependent delivery times for some single machine scheduling problems with position dependent learning effect, which are makespan are total completion. The results with respect to two algorithms proposed for solving of the each problem are compared with LINGO solutions for 50-jobs, 100-jobs and 150- jobs problems. The proposed algorithms can find the same results in shorter time.

Keywords: Delivery times, learning effect, makespan, scheduling, total completion time.

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Authors: Mahdi Hamzeh, Sied Mehdi Fakhraie, Caro Lucas

Abstract:

All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.

Keywords: Computational complexity, Deadline, Feasible scheduling, Fuzzy scheduling, Priority, Real-time multiprocessor systems, Robustness, System utilization.

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

Abstract:

In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: Real-Time Spatial Big Data, Quality Of Service, Vertical partitioning, Horizontal partitioning, Matching algorithm, Hamming distance, Stream query.

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

In this paper,the exponential passivity criteria for BAM neural networks with time-varying delays is studied.By constructing new Lyapunov-Krasovskii functional and dividing the delay interval into multiple segments,a novel sufficient condition is established to guarantee the exponential stability of the considered system.Finally,a numerical example is provided to illustrate the usefulness of the proposed main results

Keywords: BAM neural networks, Exponential passivity, LMI approach, Time-varying delays.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: Multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, Importance sampling, approximate posterior distribution, Marginal likelihood evidence.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, Pareto Optimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Peter W. Olupot, Stefan Jonsson, Joseph K. Byaruhanga

Abstract:

Porcelain specimens were fired at 6C/min to 1250C (dwell time 0.5-3h) and cooled at 6C/min to room temperature. Additionally, three different slower firing/cooling cycles were tried. Sintering profile and effects on MOR, crystalline phase content and morphology were investigated using dilatometry, 4-point bending strength, XRD and FEG-SEM respectively. Industrial-sized specimens prepared using the promising cycle were tested basing on the ANSI standards. Increasing dwell time from 1h to 3h at peak temperature of 1250C resulted in neither a significant effect on the quartz and mullite content nor MOR. Reducing the firing/cooling rate to below 6C/min, for peak temperature of 1250C (dwell time of 1h) does not result in improvement of strength of porcelain. The industrial sized specimen exhibited flashover voltages of 20.3kV (dry) and 9.3kV (wet) respectively, transverse strength of 12.5kN and bulk density of 2.27g/cm3, which are satisfactory. There was however dye penetration during porosity test. KeywordsDwell time, Microstructure, Porcelain, Strength.

Keywords: Dwell time, Microstructure, Porcelain, Strength.

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

Abstract:

Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: Time history dynamic analysis, basic modal displacement, earthquake induced demands, shear steel structures.

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Authors: Xiaoquan Ding, Jianmin Hao, Changwen Liu

Abstract:

This paper is devoted to a delayed periodic predatorprey system with non-monotonic numerical response on time scales. With the help of a continuation theorem based on coincidence degree theory, we establish easily verifiable criteria for the existence of multiple periodic solutions. As corollaries, some applications are listed. In particular, our results improve and generalize some known ones.

Keywords: Predator-prey system, periodic solution, time scale, delay, coincidence degree.

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Authors: Xin Bai, Kresimir Sivoncik, Damla Turgut, Ladislau Bölöni

Abstract:

Market based models are frequently used in the resource allocation on the computational grid. However, as the size of the grid grows, it becomes difficult for the customer to negotiate directly with all the providers. Middle agents are introduced to mediate between the providers and customers and facilitate the resource allocation process. The most frequently deployed middle agents are the matchmakers and the brokers. The matchmaking agent finds possible candidate providers who can satisfy the requirements of the consumers, after which the customer directly negotiates with the candidates. The broker agents are mediating the negotiation with the providers in real time. In this paper we present a new type of middle agent, the marketmaker. Its operation is based on two parallel operations - through the investment process the marketmaker is acquiring resources and resource reservations in large quantities, while through the resale process it sells them to the customers. The operation of the marketmaker is based on the fact that through its global view of the grid it can perform a more efficient resource allocation than the one possible in one-to-one negotiations between the customers and providers. We present the operation and algorithms governing the operation of the marketmaker agent, contrasting it with the matchmaker and broker agents. Through a series of simulations in the task oriented domain we compare the operation of the three agents types. We find that the use of marketmaker agent leads to a better performance in the allocation of large tasks and a significant reduction of the messaging overhead.

Keywords: grid computing, autonomous agents, market-basedgrid

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Authors: Seyed Hossein Iranmanesh, Zahra Mokhtari

Abstract:

Estimation time and cost of work completion in a project and follow up them during execution are contributors to success or fail of a project, and is very important for project management team. Delivering on time and within budgeted cost needs to well managing and controlling the projects. To dealing with complex task of controlling and modifying the baseline project schedule during execution, earned value management systems have been set up and widely used to measure and communicate the real physical progress of a project. But it often fails to predict the total duration of the project. In this paper data mining techniques is used predicting the total project duration in term of Time Estimate At Completion-EAC (t). For this purpose, we have used a project with 90 activities, it has updated day by day. Then, it is used regular indexes in literature and applied Earned Duration Method to calculate time estimate at completion and set these as input data for prediction and specifying the major parameters among them using Clem software. By using data mining, the effective parameters on EAC and the relationship between them could be extracted and it is very useful to manage a project with minimum delay risks. As we state, this could be a simple, safe and applicable method in prediction the completion time of a project during execution.

Keywords: Data Mining Techniques, Earned Duration Method, Earned Value, Estimate At Completion.

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Authors: B. Y. Matmuratov, S. D. Madrakhimova. R. S. Esanov. A. D. Matchanov

Abstract:

Supramolecular complexes of glycyrrhizic acid with kinetin in various molar ratios were obtained, physico-chemical parameters and spectral properties of the resulting complexes were studied (UV, IR, mass spectrometry.

Keywords: Monoammonium salt of glycyrrhizic acid, glycyrrhizic acid, supramolecular complex, isomolar series, IR spectroscopy.

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