Search results for: artificial intelligence based SCED

Authors: Enrico Rukzio, George N. Prezerakos, Giovanni Cortese, Eleftherios Koutsoloukas, Sofia Kapellaki

Abstract:

The paper focuses on the area of context modeling with respect to the specification of context-aware systems supporting ubiquitous applications. The proposed approach, followed within the SIMPLICITY IST project, uses a high-level system ontology to derive context models for system components which consequently are mapped to the system's physical entities. For the definition of user and device-related context models in particular, the paper suggests a standard-based process consisting of an analysis phase using the Common Information Model (CIM) methodology followed by an implementation phase that defines 3GPP based components. The benefits of this approach are further depicted by preliminary examples of XML grammars defining profiles and components, component instances, coupled with descriptions of respective ubiquitous applications.

Keywords: 3GPP, context, context-awareness, context model, information model, user model, XML

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Authors: Michal Mardiak, Jaroslav Polec

Abstract:

In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.

Keywords: Objective quality metrics, mutual information, region recognition, content based metrics

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Authors: Md. Z. Alam, Devi R. Asih, Md. N. Salleh

Abstract:

Immobilization of lipase enzyme produced from palm oil mill effluent (POME) by the activated carbon (AC) among the low cost support materials was optimized. The results indicated that immobilization of 94% was achieved by AC as the most suitable support material. A sequential optimization strategy based on a statistical experimental design, including one-factor-at-a-time (OFAT) method was used to determine the equilibrium time. Three components influencing lipase immobilization were optimized by the response surface methodology (RSM) based on the face-centered central composite design (FCCCD). On the statistical analysis of the results, the optimum enzyme concentration loading, agitation rate and carbon active dosage were found to be 30 U/ml, 300 rpm and 8 g/L respectively, with a maximum immobilization activity of 3732.9 U/g-AC after 2 hrs of immobilization. Analysis of variance (ANOVA) showed a high regression coefficient (R²) of 0.999, which indicated a satisfactory fit of the model with the experimental data. The parameters were statistically significant at p<0.05.

Keywords: Activated carbon, adsorption, immobilization, POME based lipase.

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco, I. Garcia-Moral

Abstract:

Robust stability and performance are the two most basic features of feedback control systems. The harmonic balance analysis technique enables to analyze the stability of limit cycles arising from a neural network control based system operating over nonlinear plants. In this work a robust stability analysis based on the harmonic balance is presented and applied to a neural based control of a non-linear binary distillation column with unstructured uncertainty. We develop ways to describe uncertainty in the form of neglected nonlinear dynamics and high harmonics for the plant and controller respectively. Finally, conclusions about the performance of the neural control system are discussed using the Nyquist stability margin together with the structured singular values of the uncertainty as a robustness measure.

Keywords: Robust stability, neural network control, unstructured uncertainty, singular values, distillation column.

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Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

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Authors: Miloje S. Radenkovic, Tamal Bose

Abstract:

This paper presents the convergence analysis of a prediction based blind equalizer for IIR channels. Predictor parameters are estimated by using the recursive least squares algorithm. It is shown that the prediction error converges almost surely (a.s.) toward a scalar multiple of the unknown input symbol sequence. It is also proved that the convergence rate of the parameter estimation error is of the same order as that in the iterated logarithm law.

Keywords: Adaptive blind equalizer, Recursive leastsquares, Adaptive Filtering, Convergence analysis.

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Authors: M. Zheng, V. S. Alagar

Abstract:

The paper discusses complexity of component-based development (CBD) of embedded systems. Although CBD has its merits, it must be augmented with methods to control the complexities that arise due to resource constraints, timeliness, and run-time deployment of components in embedded system development. Software component specification, system-level testing, and run-time reliability measurement are some ways to control the complexity.

Keywords: Components, embedded systems, complexity, softwaredevelopment, traffic controller system.

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Authors: R. Chithra, B. Kalaavathi

Abstract:

E-Learning enables the users to learn at anywhere at any time. In E-Learning systems, authenticating the E-Learning user has security issues. The usage of appropriate communication networks for providing the internet connectivity for E-learning is another challenge. WiMAX networks provide Broadband Wireless Access through the Multicast Broadcast Service so these networks can be most suitable for E-Learning applications. The authentication of E-Learning user is vulnerable to session hijacking problems. The repeated authentication of users can be done to overcome these issues. In this paper, session based Profile Caching Authentication is proposed. In this scheme, the credentials of E-Learning users can be cached at authentication server during the initial authentication through the appropriate subscriber station. The proposed cache based authentication scheme performs fast authentication by using cached user profile. Thus, the proposed authentication protocol reduces the delay in repeated authentication to enhance the security in ELearning.

Keywords: Authentication, E-Learning, WiMAX, Security, Profile caching.

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Authors: Shu-Hui Jan, Shih-Ping Ho, Hui-Ping Tserng

Abstract:

Construction knowledge can be referred to and reused among involved project managers and jobsite engineers to alleviate problems on a construction jobsite and reduce the time and cost of solving problems related to constructability. This paper proposes a new methodology to provide sharing of construction knowledge by using the Building Information Modeling (BIM) approach. The main characteristics of BIM include illustrating 3D CAD-based presentations and keeping information in a digital format, and facilitation of easy updating and transfer of information in the 3D BIM environment. Using the BIM approach, project managers and engineers can gain knowledge related to 3D BIM and obtain feedback provided by jobsite engineers for future reference. This study addresses the application of knowledge sharing management in the construction phase of construction projects and proposes a BIM-based Knowledge Sharing Management (BIMKSM) system for project managers and engineers. The BIMKSM system is then applied in a selected case study of a construction project in Taiwan to verify the proposed methodology and demonstrate the effectiveness of sharing knowledge in the BIM environment. The combined results demonstrate that the BIMKSM system can be used as a visual BIM-based knowledge sharing management platform by utilizing the BIM approach and web technology.

Keywords: Construction knowledge management, building information modeling, project management, web-based information system.

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Authors: D. Bąk-Grabowska, A. Jagoda

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Managing a capital group is a complex and specific process. It creates special conditions for the introduction of team work organization of managers. The selection of a manager employment form is a problem which gets complicated in case of management teams. The considered possibilities are an employment-based and non-employment managerial contract, which can be based on a thorough action or on formulating definite expectations regarding the results of a manager’s work. The problem of selection between individual and collegiate settlement of managers’ work has been pointed out. The deliberations were based on the assumptions of chosen company management theories, including transactional cost, agency theory, nexus of contracts theory, stewardship theory and theories referring directly to management teams, i.e. Upper echelons theory. 

Keywords: Capital group, employment forms, management teams, managers.

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Authors: Lee Feng Koo, Tze Jin Wong, Pang Hung Yiu, Nik Mohd Asri Nik Long

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Greater common divisor (GCD) attack is an attack that relies on the polynomial structure of the cryptosystem. This attack required two plaintexts differ from a fixed number and encrypted under same modulus. This paper reports a security reaction of Lucas Based El-Gamal Cryptosystem in the Elliptic Curve group over finite field under GCD attack. Lucas Based El-Gamal Cryptosystem in the Elliptic Curve group over finite field was exposed mathematically to the GCD attack using GCD and Dickson polynomial. The result shows that the cryptanalyst is able to get the plaintext without decryption by using GCD attack. Thus, the study concluded that it is highly perilous when two plaintexts have a slight difference from a fixed number in the same Elliptic curve group over finite field.

Keywords: Decryption, encryption, elliptic curve, greater common divisor.

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Authors: Mihai Duguleana, Florin Girbacia, Cristian Postelnicu, Raffaello Brodi, Marcello Carrozzino

Abstract:

Augmented Reality (AR) has taken a big leap with the introduction of mobile applications which co-locate bi-dimensional (e.g. photo, video, text) and tridimensional information with the location of the user enriching his/her experience. This study presents the advantages of using Mobile Augmented Reality (MAR) technologies in traveling applications, improving cultural heritage exploration. We propose a location-based AR application which combines co-location with the augmented visual information about Pisa monuments to establish a friendly navigation in this historic city. AR was used to render contextual visual information in the outdoor environment. The developed Android-based application offers two different options: it provides the ability to identify the monuments positioned close to the user’s position and it offers location information for getting near the key touristic objectives. We present the process of creating the monuments’ 3D map database and the navigation algorithm.

Keywords: Augmented reality, electronic compass, GPS, location-based service.

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Authors: Najm Alotaibi

Abstract:

Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: Human Motion Capture, Computer Vision, Vision based, Tracking.

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Authors: Wojciech P. Gajewski

Abstract:

The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.

Keywords: Text classification, naïve Bayesian classification, spam, email.

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Authors: Mugabe Nzarama Gabriel

Abstract:

In Rwanda, many healthcare organizations are still using a paper based patients’ data record system although it still present weaknesses to share health patients’ information across different services when necessary. In developed countries, the EHR has been put in place to revolutionize the paper based record system but still the EHR has some challenges related to privacy, security, or interoperability. The purpose of this research was to assess the existing patients’ data record system in healthcare sector in Rwanda, see what an EHR can improve to the system in place and assess the acceptance of EHR as system which is interoperable, very secure and interoperable and see whether stakeholders are ready to adopt the system. The case based methodology was used and TAM theoretical framework to design the questionnaire for the survey. A judgmental sample across two cases, CHUB and Hopital de Nemba, has been selected and SPSS has been used for descriptive statistics. After a qualitative analysis, the findings showed that the paper based record is useful, gives complete information about the patient, protects the privacy of patients but it is still less secure and less interoperable. The respondents shown that they are ready to use the proposed EHR System and want it secure, capable of enforcing the privacy but still they are not all ready for the interoperability. A conclusion has been formulated; recommendations and further research have been proposed.

Keywords: EHR system, healthcare service, TAM, privacy, interoperability.

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Authors: Razagh Hafezi, Ahmad Keshavarz, Vida Moshfegh

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This paper presents a novel algorithm of stereo correspondence with rank transform. In this algorithm we used the genetic algorithm to achieve the accurate disparity map. Genetic algorithms are efficient search methods based on principles of population genetic, i.e. mating, chromosome crossover, gene mutation, and natural selection. Finally morphology is employed to remove the errors and discontinuities.

Keywords: genetic algorithm, morphology, rank transform, stereo correspondence

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Authors: Magdi M. Nabi, Ding-Li Yu

Abstract:

This paper presents a neural network based model predictive control (MPC) strategy to control a strongly exothermic reaction with complicated nonlinear kinetics given by Chylla-Haase polymerization reactor that requires a very precise temperature control to maintain product uniformity. In the benchmark scenario, the operation of the reactor must be guaranteed under various disturbing influences, e.g., changing ambient temperatures or impurity of the monomer. Such a process usually controlled by conventional cascade control, it provides a robust operation, but often lacks accuracy concerning the required strict temperature tolerances. The predictive control strategy based on the RBF neural model is applied to solve this problem to achieve set-point tracking of the reactor temperature against disturbances. The result shows that the RBF based model predictive control gives reliable result in the presence of some disturbances and keeps the reactor temperature within a tight tolerance range around the desired reaction temperature.

Keywords: Chylla-Haase reactor, RBF neural network modelling, model predictive control.

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Authors: Guoliang Fan, Aiping Li, Xuemei Liu, Liyun Xu

Abstract:

The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.

Keywords: Complexity measurement, Kolmogorov entropy, manufacturing system, performance evaluation, tightening equipment.

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Authors: Yogesh Aggarwal

Abstract:

The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.

Keywords: Linear Regression, M5 Model Tree, Neural Network, Support Vector Machines.

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Authors: Ouadoudi Zytoune, Youssef Fakhri, Driss Aboutajdine

Abstract:

This paper focuses on reducing the power consumption of wireless sensor networks. Therefore, a communication protocol named LEACH (Low-Energy Adaptive Clustering Hierarchy) is modified. We extend LEACHs stochastic cluster-head selection algorithm by a modifying the probability of each node to become cluster-head based on its required energy to transmit to the sink. We present an efficient energy aware routing algorithm for the wireless sensor networks. Our contribution consists in rotation selection of clusterheads considering the remoteness of the nodes to the sink, and then, the network nodes residual energy. This choice allows a best distribution of the transmission energy in the network. The cluster-heads selection algorithm is completely decentralized. Simulation results show that the energy is significantly reduced compared with the previous clustering based routing algorithm for the sensor networks.

Keywords: Wireless Sensor Networks, Energy efficiency, WirelessCommunications, Clustering-based algorithm.

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Authors: Po-Chuang Chen, Hsiu-Mei Chiu, Yau-Pin Chyou, Chiou-Shia Yu

Abstract:

This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.

Keywords: Gasification, Methanol, LPMEOH, System-levelsimulation.

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Authors: V. Girondel, L. Bonnaud, A. Caplier, M. Rombaut

Abstract:

This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a naïve one and two based on the belief theory. The belief theory-based classifiers use either a classic or restricted plausibility criterion to make a decision after data fusion. The data come from the people 2D segmentation and from their face localization. Measurements consist in distances relative to a reference posture. The efficiency and the limits of the different classifiers on the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.

Keywords: Belief theory, classifiers comparison, data fusion, human motion analysis, real-time processing, static posture recognition.

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Authors: K. G. Anilkumar, T. Tanprasert

Abstract:

This paper presents a subjective job scheduler based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy alignment procedure in order formulates a real-life situation. The BPNN estimates critical values of jobs based on the given subjective criteria. The scheduler is formulated in such a way that, at each time period, the most critical job is selected from the job queue and is transferred into a single machine before the next periodic job arrives. If the selected job is one of the oldest jobs in the queue and its deadline is less than that of the arrival time of the current job, then there is an update of the deadline of the job is assigned in order to prevent the critical job from its elimination. The proposed satisfiability criteria indicates that the satisfaction of the scheduler with respect to performance of the BPNN, validity of the jobs and the feasibility of the scheduler.

Keywords: Backpropagation algorithm, Critical value, Greedy alignment procedure, Neural network, Subjective criteria, Satisfiability.

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Authors: D. Sasikala, K. Premalatha

Abstract:

The use of eXtensible Markup Language (XML) in web, business and scientific databases lead to the development of methods, techniques and systems to manage and analyze XML data. Semi-structured documents suffer due to its heterogeneity and dimensionality. XML structure and content mining represent convergence for research in semi-structured data and text mining. As the information available on the internet grows drastically, extracting knowledge from XML documents becomes a harder task. Certainly, documents are often so large that the data set returned as answer to a query may also be very big to convey the required information. To improve the query answering, a Semantic Tree Based Association Rule (STAR) mining method is proposed. This method provides intentional information by considering the structure, content and the semantics of the content. The method is applied on Reuter’s dataset and the results show that the proposed method outperforms well.

Keywords: Semi--structured Document, Tree based Association Rule (TAR), Semantic Association Rule Mining.

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Authors: Toshihiko Takemura, Atsushi Umino

Abstract:

In this paper, the authors examine whether or not there Institute for Information and Communications Policy shows are differences of Japanese Internet users awareness to information security based on individual attributes by using analysis of variance based on non-parametric method. As a result, generally speaking, it is found that Japanese Internet users' awareness to information security is different by individual attributes. Especially, the authors verify that the users who received the information security education would have rather higher recognition concerning countermeasures than other users including self-educated users. It is suggested that the information security education should be enhanced so that the users may appropriately take the information security countermeasures. In addition, the information security policy such as carrying out "e- net caravan" and "information security seminars" are effective in improving the users' awareness on the information security in Japan.

Keywords: Information security education, variance of analysis, Internet users, information security policy, Web-based survey.

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Authors: Sadaoui Djaouida

Abstract:

In the paper, the predictive control method is proposed to control the synchronization of two perturbed satellites attitude motion. Based on delayed feedback control of continuous-time systems combines with the prediction-based method of discrete-time systems, this approach only needs a single controller to realize synchronization, which has considerable significance in reducing the cost and complexity for controller implementation.

Keywords: Predictive control, Synchronization, Satellite attitude.

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Authors: S. Masteika, A.V. Rutkauskas, A. Tamosaitis

Abstract:

The paper investigates downtrend algorithm and trading strategy based on chart pattern recognition and technical analysis in futures market. The proposed chart formation is a pattern with the lowest low in the middle and one higher low on each side. The contribution of this paper lies in the reinforcement of statements about the profitability of momentum trend trading strategies. Practical benefit of the research is a trading algorithm in falling markets and back-test analysis in futures markets. When based on daily data, the algorithm has generated positive results, especially when the market had downtrend period. Downtrend algorithm can be applied as a hedge strategy against possible sudden market crashes. The proposed strategy can be interesting for futures traders, hedge funds or scientific researchers performing technical or algorithmic market analysis based on momentum trend trading.

Keywords: trading algorithm, chart pattern, downtrend trading, futures market, hedging

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Authors: Mohanchur Sakar, K.K.Shukla, K.S.Dasgupta

Abstract:

This paper attempts to establish the fact that Multi State Network Classification is essential for performance enhancement of Transport protocols over Satellite based Networks. A model to classify Multi State network condition taking into consideration both congestion and channel error is evolved. In order to arrive at such a model an analysis of the impact of congestion and channel error on RTT values has been carried out using ns2. The analysis results are also reported in the paper. The inference drawn from this analysis is used to develop a novel statistical RTT based model for multi state network classification. An Adaptive Multi State Proactive Transport Protocol consisting of Proactive Slow Start, State based Error Recovery, Timeout Action and Proactive Reduction is proposed which uses the multi state network state classification model. This paper also confirms through detail simulation and analysis that a prior knowledge about the overall characteristics of the network helps in enhancing the performance of the protocol over satellite channel which is significantly affected due to channel noise and congestion. The necessary augmentation of ns2 simulator is done for simulating the multi state network classification logic. This simulation has been used in detail evaluation of the protocol under varied levels of congestion and channel noise. The performance enhancement of this protocol with reference to established protocols namely TCP SACK and Vegas has been discussed. The results as discussed in this paper clearly reveal that the proposed protocol always outperforms its peers and show a significant improvement in very high error conditions as envisaged in the design of the protocol.

Keywords: GEO, ns2, Proactive TCP, SACK, Vegas

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Authors: Sara Zamani, Mojtaba Fazeli, Abdollah Rashidi Mehrabadi

Abstract:

In a world worried about water resources with the shadow of drought and famine looming all around, the quality of water is as important as its quantity. The source of all concerns is the constant reduction of per capita quality water for different uses. Iran With an average annual precipitation of 250 mm compared to the 800 mm world average, Iran is considered a water scarce country and the disparity in the rainfall distribution, the limitations of renewable resources and the population concentration in the margins of desert and water scarce areas have intensified the problem. The shortage of per capita renewable freshwater and its poor quality in large areas of the country, which have saline, brackish or hard water resources, and the profusion of natural and artificial pollutant have caused the deterioration of water quality. Among methods of treatment and use of these waters one can refer to the application of membrane technologies, which have come into focus in recent years due to their great advantages. This process is quite efficient in eliminating multi-capacity ions; and due to the possibilities of production at different capacities, application as treatment process in points of use, and the need for less energy in comparison to Reverse Osmosis processes, it can revolutionize the water and wastewater sector in years to come. The article studied the different capacities of water resources in the Persian Gulf and Oman Sea watershed basins, and processes the possibility of using nanofiltration process to treat brackish and non-conventional waters in these basins.

Keywords: Membrane processes, saline waters, brackish waters, hard waters, zoning water quality in the Persian Gulf and the Oman Sea Watershed area, nanofiltration.

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Authors: Samar Krimi, Kaïs Ouni, Noureddine Ellouze

Abstract:

The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a detection method that is able to detect T-waves with a sensitivity of 93% and a correct-detection ratio of 93% even with a serious amount of baseline drift and noise.

Keywords: ECG, Modulus Maxima Wavelet Transform, Performance, T-wave detection

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