Search results for: short time scale variation

Authors: Li Li, Kai-Hsuan Chu

Abstract:

It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: Real estate price, least-square, grey correlation, macroeconomics.

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Authors: Jia-Jang Wu

Abstract:

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

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

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Authors: Mohsen Ebrahimi

Abstract:

In this paper, Steam Assisted Gravity Drainage (SAGD) is introduced and its advantages over ordinary steam injection is demonstrated. A simple simulation model is built and three scenarios of natural production, ordinary steam injection, and SAGD are compared in terms of their cumulative oil production and cumulative oil steam ratio. The results show that SAGD can significantly enhance oil production in quite a short period of time. However, since the distance between injection and production wells is short, the oil to steam ratio decreases gradually through time.

Keywords: Thermal recovery, Steam injection, SAGD, Enhanced oil recovery

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Authors: Bo Wun Huang, Ah Der Lin, Yung Chuan Chen, Jao Hwa Kuang

Abstract:

The dynamic model of a drill in drilling process was proposed and investigated in this study. To assure a good drilling quality, the vibration variation on the drill tips during high speed drilling is needed to be investigated. A pre-twisted beam is used to simulate the drill. The moving Winkler-Type elastic foundation is used to characterize the tip boundary variation in drilling. Due to the variation of the drill depth, a time dependent dynamic model for the drill is proposed. Results simulated from this proposed model indicate that an abrupt natural frequencies drop are experienced as the drill tip tough the workpiece, and a severe vibration is induced. The effects of parameters, e.g. drilling speed, depth, drill size and thrust force on the drill tip responses studied.

Keywords: Drilling, vibration of drill, twisted beam

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Authors: W. Jaipahkdee, C. Srinilta

Abstract:

The overall service performance of I/O intensive system depends mainly on workload on its storage system. In heterogeneous storage environment where storage elements from different vendors with different capacity and performance are put together, workload should be distributed according to storage capability. This paper addresses data placement issue in short video sharing website. Workload contributed by a video is estimated by the number of views and life time span of existing videos in same category. Experiment was conducted on 42,000 video titles in six weeks. Result showed that the proposed algorithm distributed workload and maintained balance better than round robin and random algorithms.

Keywords: data placement, heterogeneous storage system, YouTube, short videos

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Authors: Arne Koschel, Irina Astrova, Elena Deutschkämer, Jacob Ester, Johannes Feldmann

Abstract:

In this paper various techniques in relation to large-scale systems are presented. At first, explanation of large-scale systems and differences from traditional systems are given. Next, possible specifications and requirements on hardware and software are listed. Finally, examples of large-scale systems are presented.

Keywords: Distributed file systems, cashing, large scale systems, MapReduce algorithm, NoSQL databases.

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Authors: K. Jaroensutasinee

Abstract:

The general global behavior of particle S a non-linear (Q - xy)2 potential cannot be revealed a Poincare surface of section method (PSS) because inost trajectories take practically infinitely long time to integrate numerically before they come back to the surface. In this study as an alternative to PSS, a multiple scale perturbation is applied to analyze global adiabatic, non-adiabatic and chaotic behavior of particles in this potential. It was found that the results can be summarized as a form of a Fermi-like map. Additionally, this method gives a variation of global stochasticity criteria with Q.

Keywords: Multiple Scak Perturbation The Poincare Surface or Section, Fermi Map

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Authors: Kuvshinov, D., Siswanto, A., Lozano-Parada, J., Zimmerman, W. B.

Abstract:

Ozone is well known as a powerful, fast reacting oxidant. Ozone based processes produce no by-product residual as non-reacted ozone decomposes to molecular oxygen. Therefore an application of ozone is widely accepted as one of the main approaches for a Sustainable and Clean Technologies development.

There are number of technologies which require ozone to be delivered to specific points of a production network or reactors construction. Due to space constraints, high reactivity and short life time of ozone the use of ozone generators even of a bench top scale is practically limited. This requires development of mini/micro scale ozone generator which can be directly incorporated into production units.

Our report presents a feasibility study of a new micro scale rector for ozone generation (MROG). Data on MROG calibration and indigo decomposition at different operation conditions are presented.

At selected operation conditions with residence time of 0.25 s the process of ozone generation is not limited by reaction rate and the amount of ozone produced is a function of power applied. It was shown that the MROG is capable to produce ozone at voltage level starting from 3.5kV with ozone concentration of 5.28*10^-6 (mol/L) at 5kV. This is in line with data presented on numerical investigation for a MROG. It was shown that in compare to a conventional ozone generator, MROG has lower power consumption at low voltages and atmospheric pressure.

The MROG construction makes it applicable for both submerged and dry systems. With a robust compact design MROG can be used as an integrated module for production lines of high complexity.

Keywords: DBD, micro reactor, ozone, plasma.

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Authors: Firas M. Tuaimah

Abstract:

This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity.

The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: Short-Term Load Forecasting, Artificial Neural Networks, Back propagation learning.

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Authors: Emma K. Sales, Nilda G. Butardo

Abstract:

The project was undertaken to determine the effects of modified tissue culture protocols e.g. age of culture and hormone levels (2,4-D) in generating somaclonal variation. Moreover, the utility of molecular markers (SSR and MSAP) in sorting off types/somaclones were investigated.

Results show that somaclonal variation is in effect due to prolonged subculture and high 2,4-D concentration. The resultant variation was observed to be due to high level of methylation events specifically cytosine methylation either at the internal or external cytosine and was identified by methylation sensitive amplification polymorphism (MSAP).Simple sequence repeats (SSR) on the other hand, was able to associate a marker to a trait of interest.

These therefore, show that molecular markers can be an important tool in sorting out variation/mutants at an early stage.

Keywords: Methylation, MSAP, somaclones, SSR, subculture, 2, 4-D.

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Authors: Ching-Feng Chen, Ching-Chih Tsai

Abstract:

With the size of the transistor gradually approaching the physical limit, it challenges the persistence of Moore’s Law due to such issues of the short channel effect and the development of the high numerical aperture (NA) lithography equipment. In the context of the ever-increasing technical requirements of portable devices and high-performance computing (HPC), relying on the law continuation to enhance the chip density will no longer support the prospects of the electronics industry. Weighing the chip’s power consumption-performance-area-cost-cycle time to market (PPACC) is an updated benchmark to drive the evolution of the advanced wafer nanometer (nm). The advent of two and half- and three-dimensional (2.5 and 3D)- Very-Large-Scale Integration (VLSI) packaging based on Through Silicon Via (TSV) technology has updated the traditional die assembly methods and provided the solution. This overview investigates the up-to-date and cutting-edge packaging technologies for 2.5D and 3D integrated circuits (IC) based on the updated transistor structure and technology nodes. We conclude that multi-chip solutions for 2.5D and 3D IC packaging can prolong Moore’s Law.

Keywords: Moore’s Law, High Numerical Aperture, Power Consumption-Performance-Area-Cost-Cycle Time to Market, PPACC, 2.5 and 3D-Very-Large-Scale Integration Packaging, Through Silicon Vi.

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Authors: Da-Xue Chen, Guang-Hui Liu

Abstract:

In this paper, we establish several oscillation criteria for the nonlinear second-order damped delay dynamic equation r(t)|xΔ(t)|β-1xΔ(t)Δ + p(t)|xΔσ(t)|β-1xΔσ(t) + q(t)f(x(τ (t))) = 0 on an arbitrary time scale T, where β > 0 is a constant. Our results generalize and improve some known results in which β > 0 is a quotient of odd positive integers. Some examples are given to illustrate our main results.

Keywords: Oscillation, damped delay dynamic equation, time scale.

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Authors: Khalid M. Aamir, Mohammad A. Maud

Abstract:

Power Spectral Density (PSD) of quasi-stationary processes can be efficiently estimated using the short time Fourier series (STFT). In this paper, an algorithm has been proposed that computes the PSD of quasi-stationary process efficiently using offline autoregressive model order estimation algorithm, recursive parameter estimation technique and modified sliding window discrete Fourier Transform algorithm. The main difference in this algorithm and STFT is that the sliding window (SW) and window for spectral estimation (WSA) are separately defined. WSA is updated and its PSD is computed only when change in statistics is detected in the SW. The computational complexity of the proposed algorithm is found to be lesser than that for standard STFT technique.

Keywords: Power Spectral Density (PSD), quasi-stationarytime series, short time Fourier Transform, Sliding window DFT.

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Authors: M. Zielina, W. Dabrowski, E. Radziszewska-Zielina

Abstract:

Several different cements have been tested to evaluate their potential to leach calcium, chromium and aluminum ions in soft water environment. The research allows comparing some different cements in order to the potential risk of water contamination. This can be done only in the same environment. To reach the results in reasonable short time intervals and to make heavy metals measurements with high accuracy, demineralized water was used. In this case the conditions of experiments are far away from the water supply practice, but short time experiments and measurably high concentrations of elements in the water solution are an important advantage. Moreover leaching mechanisms can be recognized, our experiments reported here refer to this kind of cements evaluation.

Keywords: Concrete corrosion, hydrogen sulfide, odors, reinforced concrete sewers, sewerage.

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Authors: T. Arudchelvam, W. W. E. N. Fernando

Abstract:

Mobile phone has become as an essential thing in our life. Therefore, security is the most important thing to be considered in mobile communication. Short message service is the cheapest way of communication via the mobile phones. Therefore, security is very important in the short message service as well. This paper presents a method to maintain the security at user level. Different types of encryption methods are used to implement the user level security in mobile phones. Caesar cipher, Rail Fence, Vigenere cipher and RSA are used as encryption methods in this work. Caesar cipher and the Rail Fence methods are enhanced and implemented. The beauty in this work is that the user can select the encryption method and the key. Therefore, by changing the encryption method and the key time to time, the user can ensure the security of messages. By this work, while users can safely send/receive messages, they can save their information from unauthorised and unwanted people in their own mobile phone as well.

Keywords: SMS, user level security, encryption, mobile communication.

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Authors: Arunee Wongkha, Suparat Niwitpong, Sa-aat Niwitpong

Abstract:

In this paper, we propose two new confidence intervals for the inverse of a normal mean with a known coefficient of variation. One of new confidence intervals for the inverse of a normal mean with a known coefficient of variation is constructed based on the pivotal statistic Z where Z is a standard normal distribution and another confidence interval is constructed based on the generalized confidence interval, presented by Weerahandi. We examine the performance of these confidence intervals in terms of coverage probabilities and average lengths via Monte Carlo simulation.

Keywords: The inverse of a normal mean, confidence interval, generalized confidence intervals, known coefficient of variation.

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Authors: M.G.A. Nassef, Linghan Li, C. Schenck, B. Kuhfuss

Abstract:

Design and modeling of nonlinear systems require the knowledge of all inside acting parameters and effects. An empirical alternative is to identify the system-s transfer function from input and output data as a black box model. This paper presents a procedure using least squares algorithm for the identification of a feed drive system coefficients in time domain using a reduced model based on windowed input and output data. The command and response of the axis are first measured in the first 4 ms, and then least squares are applied to predict the transfer function coefficients for this displacement segment. From the identified coefficients, the next command response segments are estimated. The obtained results reveal a considerable potential of least squares method to identify the system-s time-based coefficients and predict accurately the command response as compared to measurements.

Keywords: feed drive systems, least squares algorithm, onlineparameter identification, short time window

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Authors: A. Guechi, M. Chegaar

Abstract:

This study investigates how AlGaAs/GaAs thin film solar cells perform under varying global solar spectrum due to the changes of environmental parameters such as the air mass and the atmospheric turbidity. The solar irradiance striking the solar cell is simulated using the spectral irradiance model SMARTS2 (Simple Model of the Atmospheric Radiative Transfer of Sunshine) for clear skies on the site of Setif (Algeria). The results show a reduction in the short circuit current due to increasing atmospheric turbidity, it is 63.09% under global radiation. However increasing air mass leads to a reduction in the short circuit current of 81.73%. The efficiency decreases with increasing atmospheric turbidity and air mass.

Keywords: AlGaAs/GaAs, Solar Cells, Environmental parameters, Spectral Variation, SMARTS.

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Authors: Monapat Sasingha, Suttisak Soralump

Abstract:

This research presents the behavior of slope of the road along the canal stabilized by short piles. In this investigation, the centrifuge machine was used, modelling the condition of the water levels in the canal. The centrifuge tests were performed at 35 g. To observe the movement of the soil, visual analysis was performed to evaluate the failure behavior. Conclusively, the use of short piles to stabilize the canal slope proved to be an effective solution. However, the certain amount of settlement was found behind the short pile rows.

Keywords: Centrifuge test, slope failure, embankment, stability of slope.

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Authors: Isaac Cassar, Trevor Davis, Yi-Kai Lo, Wentai Liu

Abstract:

Retinal prostheses have been successful in eliciting visual responses in implanted subjects. As these prostheses progress, one of their major limitations is the need for increased resolution. As an alternative to increasing the number of electrodes, virtual electrodes may be used to increase the effective resolution of current electrode arrays. This paper presents a virtual electrode technique based upon time-offsets between stimuli. Two adjacent electrodes are stimulated with identical pulses with too short of pulse widths to activate a neuron, but one has a time offset of one pulse width. A virtual electrode of twice the pulse width was then shown to appear in the center, with a total width capable of activating a neuron. This can be used in retinal implants by stimulating electrodes with pulse widths short enough to not elicit responses in neurons, but with their combined pulse width adequate to activate a neuron in between them.

Keywords: Electrical stimulation, Neuroprosthesis, Retinal implant, Retinal Prosthesis, Virtual electrode.

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Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw

Abstract:

This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.

Keywords: Neural network, Load forecast, Time series, wavelettransform.

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Authors: M. H. Hairi, H. Zainuddin, M.H.N. Talib, A. Khamis, J. Y. Lichun

Abstract:

Short circuit currents plays a vital role in influencing the design and operation of equipment and power system and could not be avoided despite careful planning and design, good maintenance and thorough operation of the system. This paper discusses the short circuit analysis conducted in KSO briefly comprising of its significances, methods and results. A result sample of the analysis based on a single transformer is detailed in this paper. Furthermore, the results of the analysis and its significances were also discussed and commented.

Keywords: Short circuit currents, Transformer fault current

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Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

Abstract:

In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.

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Authors: Z.Farhadpour, Mohammad.R.Meybodi

Abstract:

A number of routing algorithms based on learning automata technique have been proposed for communication networks. How ever, there has been little work on the effects of variation of graph scarcity on the performance of these algorithms. In this paper, a comprehensive study is launched to investigate the performance of LASPA, the first learning automata based solution to the dynamic shortest path routing, across different graph structures with varying scarcities. The sensitivity of three main performance parameters of the algorithm, being average number of processed nodes, scanned edges and average time per update, to variation in graph scarcity is reported. Simulation results indicate that the LASPA algorithm can adapt well to the scarcity variation in graph structure and gives much better outputs than the existing dynamic and fixed algorithms in terms of performance criteria.

Keywords: Learning automata, routing, algorithm, sparse graph

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Authors: Ritu Ahlawat

Abstract:

Among all geo-hydrological relationships, rainfallrunoff relationship is of utmost importance in any hydrological investigation and water resource planning. Spatial variation, lag time involved in obtaining areal estimates for the basin as a whole can affect the parameterization in design stage as well as in planning stage. In conventional hydrological processing of data, spatial aspect is either ignored or interpolated at sub-basin level. Temporal variation when analysed for different stages can provide clues for its spatial effectiveness. The interplay of space-time variation at pixel level can provide better understanding of basin parameters. Sustenance of design structures for different return periods and their spatial auto-correlations should be studied at different geographical scales for better management and planning of water resources. In order to understand the relative effect of spatio-temporal variation in hydrological data network, a detailed geo-hydrological analysis of Betwa river catchment falling in Lower Yamuna Basin is presented in this paper. Moreover, the exact estimates about the availability of water in the Betwa river catchment, especially in the wake of recent Betwa-Ken linkage project, need thorough scientific investigation for better planning. Therefore, an attempt in this direction is made here to analyse the existing hydrological and meteorological data with the help of SPSS, GIS and MS-EXCEL software. A comparison of spatial and temporal correlations at subcatchment level in case of upper Betwa reaches has been made to demonstrate the representativeness of rain gauges. First, flows at different locations are used to derive correlation and regression coefficients. Then, long-term normal water yield estimates based on pixel-wise regression coefficients of rainfall-runoff relationship have been mapped. The areal values obtained from these maps can definitely improve upon estimates based on point-based extrapolations or areal interpolations.

Keywords: Catchment's runoff estimates, influence area regional regression coefficients, runoff yield series,

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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: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

Abstract:

In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: Inverse Analysis, Function Specification, Neural Net Works, Particle Swarm, Run Out Table.

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Authors: M. Abbaspour, D. Mansouri, N. Mansouri

Abstract:

There are reports of gas and oil wells fire due to different accidents. Many different methods are used for fire fighting in gas and oil industry. Traditional fire extinguishing techniques are mostly faced with many problems and are usually time consuming and needs lots of equipments. Besides, they cause damages to facilities, and create health and environmental problems. This article proposes innovative approach in fire extinguishing techniques in oil and gas industry, especially applicable for burning oil wells located offshore. Fire extinguishment employing a turbojet is a novel approach which can help to extinguishment the fire in short period of time. Divergent and convergent turbojets modeled in laboratory scale along with a high pressure flame were used. Different experiments were conducted to determine the relationship between output discharges of trumpet and oil wells. The results were corrected and the relationship between dimensionless parameters of flame and fire extinguishment distances and also the output discharge of turbojet and oil wells in specified distances are demonstrated by specific curves.

Keywords: Burning well, fire extinguishment, gas/oil industry, simulation.

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Authors: Ruili Zhou, Yuesheng Zhu

Abstract:

In this paper, a new robust audio fingerprinting algorithm in MP3 compressed domain is proposed with high robustness to time scale modification (TSM). Instead of simply employing short-term information of the MP3 stream, the new algorithm extracts the long-term features in MP3 compressed domain by using the modulation frequency analysis. Our experiment has demonstrated that the proposed method can achieve a hit rate of above 95% in audio retrieval and resist the attack of 20% TSM. It has lower bit error rate (BER) performance compared to the other algorithms. The proposed algorithm can also be used in other compressed domains, such as AAC.

Keywords: Audio Fingerprinting, MP3, Modulation Frequency, TSM

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Authors: Akash Rathee, Harish Parthasarathy

Abstract:

In this paper, a frequency-variation based method has been proposed for transistor parameter estimation in a commonemitter transistor amplifier circuit. We design an algorithm to estimate the transistor parameters, based on noisy measurements of the output voltage when the input voltage is a sine wave of variable frequency and constant amplitude. The common emitter amplifier circuit has been modelled using the transistor Ebers-Moll equations and the perturbation technique has been used for separating the linear and nonlinear parts of the Ebers-Moll equations. This model of the amplifier has been used to determine the amplitude of the output sinusoid as a function of the frequency and the parameter vector. Then, applying the proposed method to the frequency components, the transistor parameters have been estimated. As compared to the conventional time-domain least squares method, the proposed method requires much less data storage and it results in more accurate parameter estimation, as it exploits the information in the time and frequency domain, simultaneously. The proposed method can be utilized for parameter estimation of an analog device in its operating range of frequencies, as it uses data collected from different frequencies output signals for parameter estimation.

Keywords: Perturbation Technique, Parameter estimation, frequency-variation based method.

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