Search results for: time delay

Authors: N. Hadthamard, P. Chaumpluk, M. Buanong, P. Boonyaritthongchai, C. Wongs-Aree

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Ripe ‘Nam Dok Mai’ mango (Mangifera indica L.) is an important exported fruit of Thailand, but rapidly declined in the quality attributes mainly by infection of anthracnose and stem end rot diseases. Multilayer coating is considered as a developed technique to maintain the postharvest quality of mangoes. The utilization of alternated coating by matching oppositely electrostatic charges between 0.1% chitosan and 0.1% polystyrene sulfonate (PSS) was studied. A number of the coating layers (layer by layer) were applied on mature green ‘Nam Dok Mai No.4’ mangoes prior to storage at 25 ^oC, 65-70% relative humidity (RH). There were significant differences in some quality attributes of mangoes coated by 3½ layers, 4½ layers and 5½ layers. In comparison to coated mangoes, uncoated fruits were higher in weight loss, total soluble solids, respiration rate, ethylene production and disease incidence except the titratable acidity. Coating fruit at 3½ layers exhibited the ripening delay and reducing disease infection without off flavour. On the other hand, fruit coated with 5½ layers comprised the lowest acceptable score, caused by exhibiting disorders from fermentation at the end of storage. As a result, multilayer coating between chitosan and PSS could effectively maintain the postharvest quality of mango, but number of coating layers should be thoroughly considered.

Keywords: Multilayer, chitosan, polystyrene sulfonate, Nam Dok Mai No.4.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: Flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC).

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Authors: Rupali, Anil Kumar Jaiswal

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Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: Physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model.

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Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: Discrete time, linear estimation, Kalman filter, Kalman filter gain.

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

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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: P. T. Ahamed Seyd, V. I. Thajudin Ahamed, Jeevamma Jacob, Paul Joseph K

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Diabetes mellitus (DM) is frequently characterized by autonomic nervous dysfunction. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of autonomic nervous system (ANS). In this paper, changes in ANS activity are quantified by means of frequency and time domain analysis of R-R interval variability. Electrocardiograms (ECG) of 16 patients suffering from DM and of 16 healthy volunteers were recorded. Frequency domain analysis of extracted normal to normal interval (NN interval) data indicates significant difference in very low frequency (VLF) power, low frequency (LF) power and high frequency (HF) power, between the DM patients and control group. Time domain measures, standard deviation of NN interval (SDNN), root mean square of successive NN interval differences (RMSSD), successive NN intervals differing more than 50 ms (NN50 Count), percentage value of NN50 count (pNN50), HRV triangular index and triangular interpolation of NN intervals (TINN) also show significant difference between the DM patients and control group.

Keywords: Autonomic nervous system, diabetes mellitus, frequency domain and time domain analysis, heart rate variability.

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Authors: Rama Debbarma, Debanjan Das

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The performance of multiple tuned mass dampers to mitigate the seismic vibration of structures considering real time history data is investigated in this paper. Three different real earthquake time history data like Kobe, Imperial Valley and Mammoth Lake are taken in the present study. The multiple tuned mass dampers (MTMD) are distributed at each storey. For comparative study, single tuned mass damper (STMD) is installed at top of the similar structure. This study is conducted for a fixed mass ratio (5%) and fixed damping ratio (5%) of structures. Numerical study is performed to evaluate the effectiveness of MTMDs and overall system performance. The displacement, acceleration, base shear and storey drift are obtained for both combined system (structure with MTMD and structure with STMD) for all earthquakes. The same responses are also obtained for structure without damper system. From obtained results, it is investigated that the MTMD configuration is more effective for controlling the seismic response of the primary system with compare to STMD configuration.

Keywords: Earthquake, multiple tuned mass dampers, single tuned mass damper, time history.

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Authors: Pyotr Tsyba, Olga Razina, Ertan Güdekli, Ratbay Myrzakulov

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In this paper we consider the equation of motion for the F (R, T) gravity on their property of conformal invariance. It is shown that in the general case, such a theory is not conformal invariant. Studied special cases for the functions v and u in which can appear properties of the theory. Also we consider cosmological aspects F (R, T) theory of gravity, having considered particular case F (R, T) = μR+νT^2. Showed that in this case there is a nonlinear dependence of the parameter equation of state from time to time, which affects its evolution.

Keywords: Conformally invariance, F (R, T) gravity, metric FRW, equation of motion, dark energy.

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Authors: Aussadavut Dumrongsiri

Abstract:

Web-based technologies have created numerous opportunities for electronic word-of-mouth (eWOM) communication. There are many factors that affect customer adoption and decisionmaking process. However, only a few researches focus on some factors such as the membership time of forum and propensity to trust. Using a discrete-time event simulation to simulate a diffusion model along with a consumer decision model, the study shows the effect of each factor on adoption of opinions on on-line discussion forum. The purpose of this study is to examine the effect of factor affecting information adoption and decision making process. The model is constructed to test quantitative aspects of each factor. The simulation study shows the membership time and the propensity to trust has an effect on information adoption and purchasing decision. The result of simulation shows that the longer the membership time in the communities and the higher propensity to trust could lead to the higher demand rates because consumers find it easier and faster to trust the person in the community and then adopt the eWOM. Other implications for both researchers and practitioners are provided.

Keywords: word of mouth, simulation, consumer behavior, ebusiness, marketing, diffusion process.

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Authors: Catherine A. Todd, Fazel Naghdy

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In this work a surgical simulator is produced which enables a training otologist to conduct a virtual, real-time prosthetic insertion. The simulator provides the Ear, Nose and Throat surgeon with real-time visual and haptic responses during virtual cochlear implantation into a 3D model of the human Scala Tympani (ST). The parametric model is derived from measured data as published in the literature and accounts for human morphological variance, such as differences in cochlear shape, enabling patient-specific pre- operative assessment. Haptic modeling techniques use real physical data and insertion force measurements, to develop a force model which mimics the physical behavior of an implant as it collides with the ST walls during an insertion. Output force profiles are acquired from the insertion studies conducted in the work, to validate the haptic model. The simulator provides the user with real-time, quantitative insertion force information and associated electrode position as user inserts the virtual implant into the ST model. The information provided by this study may also be of use to implant manufacturers for design enhancements as well as for training specialists in optimal force administration, using the simulator. The paper reports on the methods for anatomical modeling and haptic algorithm development, with focus on simulator design, development, optimization and validation. The techniques may be transferrable to other medical applications that involve prosthetic device insertions where user vision is obstructed.

Keywords: Haptic modeling, medical device insertion, real-time visualization of prosthetic implantation, surgical simulation.

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Authors: Bernd Scholz-Reiter, Christian Toonen, Jan Topi Tervo, Dennis Lappe

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Time series analysis often requires data that represents the evolution of an observed variable in equidistant time steps. In order to collect this data sampling is applied. While continuous signals may be sampled, analyzed and reconstructed applying Shannon-s sampling theorem, time-discrete signals have to be dealt with differently. In this article we consider the discrete-event simulation (DES) of job-shop-systems and study the effects of different sampling rates on data quality regarding completeness and accuracy of reconstructed inventory evolutions. At this we discuss deterministic as well as non-deterministic behavior of system variables. Error curves are deployed to illustrate and discuss the sampling rate-s impact and to derive recommendations for its wellfounded choice.

Keywords: discrete-event simulation, job-shop-system, sampling rate.

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Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

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In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: Optimal linear quadratic tracker, proportional plus integral observer, state estimator, disturbance estimator.

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

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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: Rudy Agustriyanto, Akbarningrum Fatmawati

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The utilization of cheese whey as a fermentation substrate to produce bio-ethanol is an effort to supply bio-ethanol demand as a renewable energy. Like other process systems, modeling is also required for fermentation process design, optimization and plant operation. This research aims to study the fermentation process of cheese whey by applying mathematics and fundamental concept in chemical engineering, and to investigate the characteristic of the cheese whey fermentation process. Steady state simulation results for inlet substrate concentration of 50, 100 and 150 g/l, and various values of hydraulic retention time, showed that the ethanol productivity maximum values were 0.1091, 0.3163 and 0.5639 g/l.h respectively. Those values were achieved at hydraulic retention time of 20 hours, which was the minimum value used in this modeling. This showed that operating reactor at low hydraulic retention time was favorable. Model of bio-ethanol production from cheese whey will enhance the understanding of what really happen in the fermentation process.

Keywords: Cheese whey, ethanol, fermentation, modeling.

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

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The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: Group formation, group commerce, mobile commerce, So-Lo-Mo, social influence.

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Authors: Bassma Aldahlan, Zongming Fei

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Recently, there is a great interest in smart parking application. Theses applications are enhanced by a vehicular ad-hoc network, which helps drivers find and reserve satiable packing spaces for a period of time ahead of time. Named Data Networking (NDN) is a future Internet architecture that benefits vehicular ad-hoc networks because of its clean-slate design and pure communication model. In this paper, we proposed an NDN-based frame-work for smart parking that involved a fog computing architecture. The proposed application had two main directions: First, we allowed drivers to query the number of parking spaces in a particular parking lot. Second, we introduced a technique that enabled drivers to make intelligent reservations before their arrival time. We also introduced a “push-based” model supporting the NDN-based framework for smart parking applications. To evaluate the proposed solution’s performance, we analyzed the function for finding parking lots with available parking spaces and the function for reserving a parking space. Our system showed high performance results in terms of response time and push overhead. The proposed reservation application performed better than the baseline approach.

Keywords: Cloud Computing, Vehicular Named Data Networking, Smart Parking Applications, Fog Computing.

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Authors: Kyung Hyun, Choi, Minh Ngoc, Nong, M. Asif Ali, Rehmani

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This present paper proposes the modified Elastic Strip method for mobile robot to avoid obstacles with a real time system in an uncertain environment. The method deals with the problem of robot in driving from an initial position to a target position based on elastic force and potential field force. To avoid the obstacles, the robot has to modify the trajectory based on signal received from the sensor system in the sampling times. It was evident that with the combination of Modification Elastic strip and Pseudomedian filter to process the nonlinear data from sensor uncertainties in the data received from the sensor system can be reduced. The simulations and experiments of these methods were carried out.

Keywords: Collision avoidance, Avoidance obstacle, Elastic Strip, Real time collision avoidance.

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Authors: J. Barbarán, M. Díaz, I. Esteve, D. Garrido, L. Llopis, B. Rubio

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Wireless Sensor and Actor Networks (WSANs) constitute an emerging and pervasive technology that is attracting increasing interest in the research community for a wide range of applications. WSANs have two important requirements: coordination interactions and real-time communication to perform correct and timely actions. This paper introduces a methodology to facilitate the task of the application programmer focusing on the coordination and real-time requirements of WSANs. The methodology proposed in this model uses a real-time component model, UM-RTCOM, which will help us to achieve the design and implementation of applications in WSAN by using the component oriented paradigm. This will help us to develop software components which offer some very interesting features, such as reusability and adaptability which are very suitable for WSANs as they are very dynamic environments with rapidly changing conditions. In addition, a high-level coordination model based on tuple channels (TC-WSAN) is integrated into the methodology by providing a component-based specification of this model in UM-RTCOM; this will allow us to satisfy both sensor-actor and actor-actor coordination requirements in WSANs. Finally, we present in this paper the design and implementation of an application which will help us to show how the methodology can be easily used in order to achieve the development of WSANs applications.

Keywords: Sensor networks, real time and embedded systems.

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Authors: Roberta Ranielle M. de Freitas, Vagner R. Botaro

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The relationship between biodegradation and mechanical behavior is fundamental for studies of the application of cellulose acetate films as a possible material for biodegradable packaging. In this work, the biodegradation of cellulose acetate (CA) with DS 2.5 was analyzed in simulated soil. CA films were prepared by casting and buried in the simulated soil. Samples were taken monthly and analyzed, the total time of biodegradation was 6 months. To characterize the biodegradable CA, the DMA technique was employed. The main result showed that the time of exposure to the simulated soil affects the mechanical properties of the films and the values of crystallinity. By DMA analysis, it was possible to conclude that as the CA is biodegraded, its mechanical properties were altered, for example, storage modulus has increased with biodegradation and the modulus of loss has decreased. Analyzes of DSC, XRD, and FTIR were also carried out to characterize the biodegradation of CA, which corroborated with the results of DMA. The observation of the carbonyl band by FTIR and crystalline indices obtained by XRD were important to evaluate the degradation of CA during the exposure time.

Keywords: Biodegradation, cellulose acetate, DMA, simulated soil.

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Authors: Yu-Hsin Chen, Yuan-Tai Hsieh, Cheng-Shong Hong, Chia-Ching Wu, Cheng-Fu Yang, Yu-Jhen Liou

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In this study, we investigated (In,Ga,Zn)O_x (IGZO) thin films and examined their characteristics of using Ga₂O₃-2 ZnO (GZO) co-sputtered In₂O₃ prepared by dual target radio frequency magnetron sputtering at room temperature in a pure Ar atmosphere. RF powers of 80 W and 70 W were used for GZO and pure In₂O₃, room temperature (RT) was used as deposition temperature, and the deposition time was changed from 15 min to 60 min. Structural, surface, electrical, and optical properties of IGZO thin films were investigated as a function of deposition time. Furthermore, the GZO co-sputtered In₂O₃ thin films showed a very smooth and featureless surface and an amorphous structure regardless of the deposition time due to the room temperature sputtering process. We would show that the co-sputtered IGZO thin films exhibited transparent electrode properties with high transmittance ratio and low resistivity.

Keywords: IGZO, co-sputter, Ga2O3-2 ZnO, In2O3.

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Authors: Farzaneh Ahmadzadeh

Abstract:

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage

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Authors: E. Farshidi, N. Ahmadpoor

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In this paper, a alternative structure method for continuous time sigma delta modulator is presented. In this modulator for implementation of integrators in loop filter second generation current conveyors are employed. The modulator is designed in CMOS technology and features low power consumption (<2.8mW), low supply voltage (±1.65), wide dynamic range (>65db), and with 180khZ bandwidth. Simulation results confirm that this design is suitable for data converters.

Keywords: Current Conveyor, continuous, sigma delta, MOS, modulator

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Authors: Jamal Wiwoho, Pujiyono, Triyanto

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Terrorism is a real enemy for all countries, including Indonesia. Bomb attacks in some parts of Indonesia are proof that Indonesia has serious problems with terrorism. Perpetrators of terror are arrested and imprisoned, and some of them were executed. However, this method did not succeed in stopping the terrorist attacks. Former terrorists continue to carry out bomb attacks. Therefore, this paper proposes a program towards deradicalization efforts of former terrorists through entrepreneurship. This is necessary because it is impossible to change their radical ideology. The program is also motivated by understanding that terrorists generally come from poor families. This program aims to occupy their time with business activities so there is no time to plan and carry out bomb attacks. This research is an empirical law study. Data were collected by literature study, observation, and in-depth interviews. Data were analyzed with the Miles and Huberman interactive model. The results show that the entrepreneurship program is effective to prevent terrorist attack. Former terrorists are busy with their business. Therefore, they have no time to carry out bomb attacks.

Keywords: Deradicalization, terrorists, entrepreneurship.

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Authors: R. Tlili Yaakoubi, H. Nakouri, O. Blanpain, S. Lallahem

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: Automation, optimization, paradigm, RTC.

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Authors: Madina Hamiane, Amina Khunji

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Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This paper presents an application of image processing techniques to implement a real-time change detection system. Change is identified by comparing the RGB representation of two consecutive frames captured in real-time. The detection threshold can be controlled to account for various luminance levels. The comparison result is passed through a filter before decision making to reduce false positives, especially at lower luminance conditions. The system is implemented with a MATLAB Graphical User interface with several controls to manage its operation and performance.

Keywords: Image change detection, Image processing, image filtering, thresholding, B/W quantization.

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Authors: Sh. Hosseini, M. B. Limooei, M. Hossein Zade, E. Askarnia, Z. Asadi

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Manganese steel (Hadfield) is one of the important alloys in industry due to its special properties. High work hardening ability with appropriate toughness and ductility are the properties that caused this alloy to be used in wear resistance parts and in high strength condition. Heat treatment is the main process through which the desired mechanical properties and microstructures are obtained in Hadfield steel. In this study various heat treatment cycles, differing in austenising temperature, time and quenching solution are applied. For this purpose, the same samples of manganese steel was heat treated in 9 different cycles, and then the mechanical properties and microstructures were investigated. Based on the results of the study, the optimum heat treatment cycle was obtained.

Keywords: Manganese steel (Hadfield), heat treatment, austenising temperature, austenising time, quenching solution, mechanical properties.

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Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

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Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: Aerial robots, Motion primitives, Robotics.

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Authors: Sarun Phibanchon

Abstract:

The solitary wave solution of the quadratic nonlinear Schrdinger equation is determined by the iterative method called Petviashvili method. This solution is also used for the initial condition for the time evolution to study the stability analysis. The spectral method is applied for the time evolution.

Keywords: soliton, iterative method, spectral method, plasma

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: Time series modelling, ARIMA model, River runoff, Karkheh River, CLS method.

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