Search results for: Freeman Chain Code andFeedforward Backpropagation Neural Networks.

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

Abstract:

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: Cancer classification, feature selection, deep learning, genetic algorithm.

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Authors: P. Parvizi, F. Norouzifard, S.Mohammadi

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The need to implement intelligent highways is much more emphasized with the growth of vehicle production line as well as vehicle intelligence. The control of intelligent vehicles in order to reduce human error and boost ease congestion is not accomplished solely by the aid of human resources. The present article is an attempt to introduce an intelligent control system based on a single central computer. In this project, central computer, without utilizing Global Positioning System (GPS), is capable of tracking all vehicles, crisis management and control, traffic guidance and recording traffic crimes along the highway. By the help of RFID technology, vehicles are connected to computerized systems, intelligent light poles and other available hardware along the way. By the aid of Wimax communicative technology, all components of the system are virtually connected together through local and global networks devised in them and the energy of the network is provided by the solar cells installed on the intelligent light poles.

Keywords: intelligent highway, intelligent light pole, highway automation

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Authors: M. Nayeripour, T. Niknam

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Nonlinear and unbalance loads in three phase networks create harmonics and losses. Active and passive filters are used for elimination or reduction of these effects. Passive filters have some limitations. For example, they are designed only for a specific frequency and they may cause to resonance in the network at the point of common coupling. The other drawback of a passive filter is that the sizes of required elements are normally large. The active filter can improve some of limitations of passive filter for example; they can eliminate more than one harmonic and don't cause resonance in the network. In this paper inverter analysis have been done simultaneously in three phase and the RL impedance of the line have been considered. A sliding mode control based on energy feedback of capacitors is employed in the design with this method, the dynamic speed of the filter is improved effectively and harmonics and load unbalance is compensating quickly.

Keywords: Shunt active filter, harmonic, inverter, sliding mode control, energy feedback.

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Authors: M. Ahmadi Marvast, M. Sohrabi, H. Ganji

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The rate of production of main products of the Fischer-Tropsch reactions over Fe/HZSM5 bifunctional catalyst in a fixed bed reactor is investigated at a broad range of temperature, pressure, space velocity, H2/CO feed molar ratio and CO2, CH4 and water flow rates. Model discrimination and parameter estimation were performed according to the integral method of kinetic analysis. Due to lack of mechanism development for Fisher – Tropsch Synthesis on bifunctional catalysts, 26 different models were tested and the best model is selected. Comprehensive one and two dimensional heterogeneous reactor models are developed to simulate the performance of fixed-bed Fischer – Tropsch reactors. To reduce computational time for optimization purposes, an Artificial Feed Forward Neural Network (AFFNN) has been used to describe intra particle mass and heat transfer diffusion in the catalyst pellet. It is seen that products' reaction rates have direct relation with H2 partial pressure and reverse relation with CO partial pressure. The results show that the hybrid model has good agreement with rigorous mechanistic model, favoring that the hybrid model is about 25-30 times faster.

Keywords: Fischer-Tropsch, heterogeneous modeling, kinetic study.

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Authors: Sungjin Lee, Donghyun Choi, Choonsik Park, Seungjoo Kim

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A SCADA (Supervisory Control And Data Acquisition) system is an industrial control and monitoring system for national infrastructures. The SCADA systems were used in a closed environment without considering about security functionality in the past. As communication technology develops, they try to connect the SCADA systems to an open network. Therefore, the security of the SCADA systems has been an issue. The study of key management for SCADA system also has been performed. However, existing key management schemes for SCADA system such as SKE(Key establishment for SCADA systems) and SKMA(Key management scheme for SCADA systems) cannot support broadcasting communication. To solve this problem, an Advanced Key Management Architecture for Secure SCADA Communication has been proposed by Choi et al.. Choi et al.-s scheme also has a problem that it requires lots of computational cost for multicasting communication. In this paper, we propose an enhanced scheme which improving computational cost for multicasting communication with considering the number of keys to be stored in a low power communication device (RTU).

Keywords: SCADA system, SCADA communication, Key management, Distributed networks.

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Authors: M. Izvercianu, L. Ivascu

Abstract:

This paper presents an innovative computer system that contributes to sustainable development of the enterprise. The research refers to a rethinking of traditional systems of collaboration and risk assessment, present in any organization, leading to a sustainable enterprise. This concept integrates emerging tools that allow the implementation and exploitation of the collective intelligence of the enterprise, allowing the exchange of contextual, agile and simplified information, and collaboration with networks of customers and partners in an environment where risks are controlled. Risk assessment is done in a systemic way: the enterprise as the system compared to the contained departments and the enterprise as a subsystem compared to: families of international standards and sustainability-s responsibilities. The enterprise, in this systemic vision, responds to the requirements that any existing system to operate continuously in an indefinite future without reaching key resource depletion. The research is done by integrating collaborative science, engineering, management, psychology, obtaining thus a cornerstone of sustainable development of the enterprise.

Keywords: Enterprise 2.0, ISO, Risk management, Sustainable development

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Authors: A. Khodabakhshi, A. Mortazavi

Abstract:

Accurate determination of rock mass deformation modulus, as an important design parameter, is one of the most controversial issues in most engineering projects. A 3D numerical model of standard plate load test (PLT) using the FLAC3D code was carried to investigate the mechanism governing the test process. Five objectives were the focus of this study. The first goal was to employ 3D modeling in the interpretation of PLT conducted at the Bazoft dam site, Iran. The second objective was to investigate the effect of displacements measuring depth from the loading plates on the calculated moduli. The magnitude of rock mass deformation modulus calculated from PLT depends on anchor depth, and in practice, this may be a cause of error in the selection of realistic deformation modulus for the rock mass. The third goal of the study was to investigate the effect of testing plate diameter on the calculated modulus. Moreover, a comparison of the calculated modulus from ISRM formula, numerical modeling and calculated modulus from the actual PLT carried out at right abutment of the Bazoft dam site was another objective of the study. Finally, the effect of plastic strains on the calculated moduli in each of the loading-unloading cycles for three loading plates was investigated. The geometry, material properties, and boundary conditions on the constructed 3D model were selected based on the in-situ conditions of PLT at Bazoft dam site. A good agreement was achieved between numerical model results and the field tests results.

Keywords: Deformation modulus, numerical model, plate loading test, rock mass.

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Authors: Taha Landolsi, A. R. Al-Ali, Tarik Ozkul, Mohammad A. Al-Rousan

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In this paper, we present a cost-effective wireless distributed load shedding system for non-emergency scenarios. In power transformer locations where SCADA system cannot be used, the proposed solution provides a reasonable alternative that combines the use of microcontrollers and existing GSM infrastructure to send early warning SMS messages to users advising them to proactively reduce their power consumption before system capacity is reached and systematic power shutdown takes place. A novel communication protocol and message set have been devised to handle the messaging between the transformer sites, where the microcontrollers are located and where the measurements take place, and the central processing site where the database server is hosted. Moreover, the system sends warning messages to the endusers mobile devices that are used as communication terminals. The system has been implemented and tested via different experimental results.

Keywords: Smart Grid, Load shedding, Demand SideManagement, GSM Wireless Networks, SCADA systems.

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Authors: Bohsiu Wu

Abstract:

Among serious crimes, child homicide is a rather rare event. However, the killing of children stirs up a special type of emotion in society that pales other criminal acts. This study examines the relevancy of three possible community-level explanations for child homicide: social deprivation, female empowerment, and social isolation. The social deprivation hypothesis posits that child homicide results from lack of resources in communities. The female empowerment hypothesis argues that a higher female status translates into a higher level of capability to prevent child homicide. Finally, the social isolation hypothesis regards child homicide as a result of lack of social connectivity. Child homicide data, aggregated by US postal ZIP codes in California from 1990 to 1999, were analyzed with a negative binomial regression. The results of the negative binomial analysis demonstrate that social deprivation is the most salient and consistent predictor among all other factors in explaining child homicide victimization at the ZIP-code level. Both social isolation and female labor force participation are weak predictors of child homicide victimization across communities. Further, results from the negative binomial regression show that it is the communities with a higher, not lower, degree of female labor force participation that are associated with a higher count of child homicide. It is possible that poor communities with a higher level of female employment have a lesser capacity to provide the necessary care and protection for the children. Policies aiming at reducing social deprivation and strengthening female empowerment possess the potential to reduce child homicide in the community.

Keywords: Child homicide, deprivation, empowerment, isolation.

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Authors: M. Khosravy-el-Hossani, Q. Dorosti

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One of the important applications of gas turbines is their utilization for heat recovery steam generator in combine-cycle technology. Exhaust flow and energy are two key parameters for determining heat recovery steam generator performance which are mainly determined by the main gas turbine components performance data. For this reason a method was developed for determining the exhaust energy in the new edition of ASME PTC22. The result of this investigation shows that the method of standard has considerable error. Therefore in this paper a new method is presented for modifying of the performance calculation. The modified method is based on exhaust gas constituent analysis and combustion calculations. The case study presented here by two kind of General Electric gas turbine design data for validation of methodologies. The result shows that the modified method is more precise than the ASME PTC22 method. The exhaust flow calculation deviation from design data is 1.5-2 % by ASME PTC22 method so that the deviation regarding with modified method is 0.3-0.5%. Based on precision of analyzer instruments, the method can be suitable alternative for gas turbine standard performance test. In advance two methods are proposed based on known and unknown fuel in modified method procedure. The result of this paper shows that the difference between the two methods is below than %0.02. In according to reasonable esult of the second procedure (unknown fuel composition), the method can be applied to performance evaluation of gas turbine, so that the measuring cost and data gathering should be reduced.

Keywords: Gas turbine, Performance test code, Combined cycle.

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Authors: Ghassan A. Abed, Mahamod Ismail, Kasmiran Jumari

Abstract:

Long Term Evolution (LTE) is a 4G wireless broadband technology developed by the Third Generation Partnership Project (3GPP) release 8, and it's represent the competitiveness of Universal Mobile Telecommunications System (UMTS) for the next 10 years and beyond. The concepts for LTE systems have been introduced in 3GPP release 8, with objective of high-data-rate, low-latency and packet-optimized radio access technology. In this paper, performance of different TCP variants during LTE network investigated. The performance of TCP over LTE is affected mostly by the links of the wired network and total bandwidth available at the serving base station. This paper describes an NS-2 based simulation analysis of TCP-Vegas, TCP-Tahoe, TCPReno, TCP-Newreno, TCP-SACK, and TCP-FACK, with full modeling of all traffics of LTE system. The Evaluation of the network performance with all TCP variants is mainly based on throughput, average delay and lost packet. The analysis of TCP performance over LTE ensures that all TCP's have a similar throughput and the best performance return to TCP-Vegas than other variants.

Keywords: LTE; EUTRAN; 3GPPP, SAE; TCP Variants; NS-2

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Authors: Muhammad R. Ahmed, Xu Huang, Dharmendra Sharma

Abstract:

Despite extensive study on wireless sensor network security, defending internal attacks and finding abnormal behaviour of the sensor are still difficult and unsolved task. The conventional cryptographic technique does not give the robust security or detection process to save the network from internal attacker that cause by abnormal behavior. The insider attacker or abnormally behaved sensor identificationand location detection framework using false massage detection and Time difference of Arrival (TDoA) is presented in this paper. It has been shown that the new framework can efficiently identify and detect the insider attacker location so that the attacker can be reprogrammed or subside from the network to save from internal attack.

Keywords: Insider Attaker identification, Abnormal Behaviour, Location detection, Time difference of Arrival (TDoA), Wireless sensor network

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

Abstract:

This work aims to compare various techniques used in order to mitigate Inter-Cell Interference (ICI) in Long Term Evolution (LTE) and LTE-Advanced systems. For that, we will evaluate the performance of each one. In mobile communication networks, systems are limited by ICI particularly caused by deployment of small cells in conventional cell’s implementation. Therefore, various mitigation techniques, named Inter-Cell Interference Coordination techniques (ICIC), enhanced Inter-Cell Interference Coordination (eICIC) techniques and Coordinated Multi-Point transmission and reception (CoMP) are proposed. This paper presents a comparative study of these strategies. It can be concluded that CoMP techniques can ameliorate SINR and capacity system compared to ICIC and eICIC. In fact, SINR value reaches 15 dB for a distance of 0.5 km between user equipment and servant base station if we use CoMP technology whereas it cannot exceed 12 dB and 9 dB for eICIC and ICIC approaches respectively as reflected in simulations.

Keywords: 4th generation, interference, coordination, ICIC.

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Authors: Varsha Shah, Patel Pritesh, Patel Sagar, PrasantaKundu, RanjanMaheshwari

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Performance of vehicle depends on driving patterns and vehicle drive train configuration. Driving patterns depends on traffic condition, road condition and driver behavior. HEV design is carried out under certain constrain like vehicle operating range, acceleration, decelerations, maximum speed and road grades which are directly related to the driving patterns. Therefore the detailed study on HEV performance over a different drive cycle is required for selection and sizing of HEV components. A simple hardware is design to measured velocity v/s time profile of the vehicle by operating vehicle on Indian roads under real traffic conditions. To size the HEV components, a detailed dynamic model of the vehicle is developed considering the effect of inertia of rotating components like wheels, drive chain, engine and electric motor. Using vehicle model and different Indian drive cycles data, total tractive power demanded by vehicle and power supplied by individual components has been calculated.Using above information selection and estimation of component sizing for HEV is carried out so that HEV performs efficiently under hostile driving condition. Complete analysis is carried out in LABVIEW.

Keywords: BLDC motor, Driving cycle, LABVIEW Ultracapacitors, Vehicle Dynamics,

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Authors: Françoise Petersen, Mike Pluke, Tatiana Kovacikova, Giovanni Bartolomeo

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As communications systems and technology become more advanced and complex, it will be increasingly important to focus on users- individual needs. Personalization and effective user profile management will be necessary to ensure the uptake and success of new services and devices and it is therefore important to focus on the users- requirements in this area and define solutions that meet these requirements. The work on personalization and user profiles emerged from earlier ETSI work on a Universal Communications Identifier (UCI) which is a unique identifier of the user rather than a range of identifiers of the many of communication devices or services (e.g. numbers of fixed phone at home/work, mobile phones, fax and email addresses). This paper describes work on personalization including standardized information and preferences and an architectural framework providing a description of how personalization can be integrated in Next Generation Networks, together with the UCI concept.

Keywords: Interoperability, Next Generation Network (NGN), Personalization, Universal Communications Identifier (UCI), User Profile Management (UPM)

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: Criminal digital evidence, social media, ontologies, reasoning.

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Authors: P. Jomsri

Abstract:

Currently, web usage make a huge data from a lot of user attention. In general, proxy server is a system to support web usage from user and can manage system by using hit rates. This research tries to improve hit rates in proxy system by applying data mining technique. The data set are collected from proxy servers in the university and are investigated relationship based on several features. The model is used to predict the future access websites. Association rule technique is applied to get the relation among Date, Time, Main Group web, Sub Group web, and Domain name for created model. The results showed that this technique can predict web content for the next day, moreover the future accesses of websites increased from 38.15% to 85.57 %. This model can predict web page access which tends to increase the efficient of proxy servers as a result. In additional, the performance of internet access will be improved and help to reduce traffic in networks.

Keywords: Association rule, proxy server, data mining.

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

Abstract:

The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: National development, granite, profitability assessment, ANN models.

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Authors: Sushil Sarwa, Rajeev Kumar

Abstract:

The wireless mesh networks (WMNs) are emerging technology in wireless networking as they can serve large scale high speed internet access. Due to its wireless multi-hop feature, wireless mesh network is prone to suffer from many attacks, such as denial of service attack (DoS). We consider a special case of DoS attack which is selective forwarding attack (a.k.a. gray hole attack). In such attack, a misbehaving mesh router selectively drops the packets it receives rom its predecessor mesh router. It is very hard to detect that packet loss is due to medium access collision, bad channel quality or because of selective forwarding attack. In this paper, we present a review of detection algorithms of selective forwarding attack and discuss their advantage & disadvantage. Finally we conclude this paper with open research issues and challenges.

Keywords: CAD algorithm, CHEMAS, selective forwarding attack, watchdog & pathrater, wireless mesh network.

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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Authors: Payam Nabhani, Sima Radmanesh

Abstract:

Opportunistic network is a kind of Delay Tolerant Networks (DTN) where the nodes in this network come into contact with each other opportunistically and communicate wirelessly and, an end-to-end path between source and destination may have never existed, and disconnection and reconnection is common in the network. In such a network, because of the nature of opportunistic network, perhaps there is no a complete path from source to destination for most of the time and even if there is a path; the path can be very unstable and may change or break quickly. Therefore, routing is one of the main challenges in this environment and, in order to make communication possible in an opportunistic network, the intermediate nodes have to play important role in the opportunistic routing protocols. In this paper we proposed an Adaptive Fuzzy Routing in opportunistic network (AFRON). This protocol is using the simple parameters as input parameters to find the path to the destination node. Using Message Transmission Count, Message Size and Time To Live parameters as input fuzzy to increase delivery ratio and decrease the buffer consumption in the all nodes of network.

Keywords: Opportunistic Routing, Fuzzy Routing, Opportunistic Network, Message Routing.

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Authors: Mussa Mahmoudi

Abstract:

For Seismic design, it is important to estimate, maximum lateral displacement (inelastic displacement) of the structures due to sever earthquakes for several reasons. Seismic design provisions estimate the maximum roof and storey drifts occurring in major earthquakes by amplifying the drifts of the structures obtained by elastic analysis subjected to seismic design load, with a coefficient named “displacement amplification factor" which is greater than one. Here, this coefficient depends on various parameters, such as ductility and overstrength factors. The present research aims to evaluate the value of the displacement amplification factor in seismic design codes and then tries to propose a value to estimate the maximum lateral structural displacement from sever earthquakes, without using non-linear analysis. In seismic codes, since the displacement amplification is related to “force reduction factor" hence; this aspect has been accepted in the current study. Meanwhile, two methodologies are applied to evaluate the value of displacement amplification factor and its relation with the force reduction factor. In the first methodology, which is applied for all structures, the ratio of displacement amplification and force reduction factors is determined directly. Whereas, in the second methodology that is applicable just for R/C moment resisting frame, the ratio is obtained by calculating both factors, separately. The acquired results of these methodologies are alike and estimate the ratio of two factors from 1 to 1.2. The results indicate that the ratio of the displacement amplification factor and the force reduction factor differs to those proposed by seismic provisions such as NEHRP, IBC and Iranian seismic code (standard no. 2800).

Keywords: Displacement amplification factor, Ductility factor, Force reduction factor, Maximum lateral displacement.

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Authors: M. Sadighi, H. Pouriayevali, M. Saadati

Abstract:

This paper deals with analysis of flexural stiffness, indentation and their energies in three point loading of sandwich beams with composite faces from Eglass/epoxy and cores from Polyurethane or PVC. Energy is consumed in three stages of indentation in laminated beam, indentation of sandwich beam and bending of sandwich beam. Theory of elasticity is chosen to present equations for indentation of laminated beam, then these equations have been corrected to offer better results. An analytical model has been used assuming an elastic-perfectly plastic compressive behavior of the foam core. Classical theory of beam is used to describe three point bending. Finite element (FE) analysis of static indentation sandwich beams is performed using the FE code ABAQUS. The foam core is modeled using the crushable foam material model and response of the foam core is experimentally characterized in uniaxial compression. Three point bending and indentation have been done experimentally in two cases of low velocity and higher velocity (quasi-impact) of loading. Results can describe response of beam in terms of core and faces thicknesses, core material, indentor diameter, energy absorbed, and length of plastic area in the testing. The experimental results are in good agreement with the analytical and FE analyses. These results can be used as an introduction for impact loading and energy absorbing of sandwich structures.

Keywords: Three point Bending, Indentation, Foams, Composite laminated beam, Sandwich beams, Finite element

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Authors: Sareh Rajabi, Salwa Bheiry

Abstract:

In general, Covid-19 created many financial and non-financial damages to the economy and community. Level and severity of covid-19 as pandemic case varies over the region and due to different types of the projects. Covid-19 virus emerged as one of the most imperative risk management factors word-wide recently. Therefore, as part of portfolio management assessment, it is essential to evaluate severity of such risk on the project and program in portfolio management level to avoid any risky portfolio. Covid-19 appeared very effectively in South America, part of Europe and Middle East. Such pandemic infection affected the whole universe, due to lock down, interruption in supply chain management, health and safety requirements, transportations and commercial impacts. Therefore, this research proposes Analytical Hierarchy Process (AHP) to analyze and assess such pandemic case like Covid-19 and its impacts on the construction projects. The AHP technique uses four sub-criteria: Health and safety, commercial risk, completion risk and contractual risk to evaluate the project and program. The result will provide the decision makers with information which project has higher or lower risk in case of Covid-19 and pandemic scenario. Therefore, the decision makers can have most feasible solution based on effective weighted criteria for project selection within their portfolio to match with the organization’s strategies.

Keywords: Portfolio management, risk management, COVID-19, analytical hierarchy process technique.

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Authors: Sheena Christabel Pravin, M. Palanivelan

Abstract:

Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: Bilingual, children who stutter, children with language impairment, Hidden Markov Models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies.

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Authors: Sunmyeng Kim

Abstract:

IEEE 802.11a/b/g standards support multiple transmission rates. Even though the use of multiple transmission rates increase the WLAN capacity, this feature leads to the performance anomaly problem. Cooperative communication was introduced to relieve the performance anomaly problem. Data packets are delivered to the destination much faster through a relay node with high rate than through direct transmission to the destination at low rate. In the legacy cooperative protocols, a source node chooses a relay node only based on the transmission rate. Therefore, they are not so feasible in multi-flow environments since they do not consider the effect of other flows. To alleviate the effect, we propose a new relay node selection algorithm based on the transmission rate and channel contention level. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and delay.

Keywords: Cooperative communications, MAC protocol, Relay node, WLAN.

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Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar

Abstract:

Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.

To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.

It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.

Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.

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Authors: W. Adi, Khaled E. A. Negm, A. Mabrouk, H. Ghraieb

Abstract:

In the current study we present a system that is capable to deliver proxy based differentiated service. It will help the carrier service node to sell a prepaid service to clients and limit the use to a particular mobile device or devices for a certain time. The system includes software and hardware architecture for a mobile device with moderate computational power, and a secure protocol for communication between it and its carrier service node. On the carrier service node a proxy runs on a centralized server to be capable of implementing cryptographic algorithms, while the mobile device contains a simple embedded processor capable of executing simple algorithms. One prerequisite is needed for the system to run efficiently that is a presence of Global Trusted Verification Authority (GTVA) which is equivalent to certifying authority in IP networks. This system appears to be of great interest for many commercial transactions, business to business electronic and mobile commerce, and military applications.

Keywords: Mobile Device Security, Identity Authentication, Mobile Commerce Security.

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Authors: A. Bendarma, T. Jankowiak, A. Rusinek, T. Lodygowski, M. Klósak, S. Bouslikhane

Abstract:

The analysis of the mechanical characteristics and dynamic behavior of aluminum alloy sheet due to perforation tests based on the experimental tests coupled with the numerical simulation is presented. The impact problems (penetration and perforation) of the metallic plates have been of interest for a long time. Experimental, analytical as well as numerical studies have been carried out to analyze in details the perforation process. Based on these approaches, the ballistic properties of the material have been studied. The initial and residual velocities laser sensor is used during experiments to obtain the ballistic curve and the ballistic limit. The energy balance is also reported together with the energy absorbed by the aluminum including the ballistic curve and ballistic limit. The high speed camera helps to estimate the failure time and to calculate the impact force. A wide range of initial impact velocities from 40 up to 180 m/s has been covered during the tests. The mass of the conical nose shaped projectile is 28 g, its diameter is 12 mm, and the thickness of the aluminum sheet is equal to 1.0 mm. The ABAQUS/Explicit finite element code has been used to simulate the perforation processes. The comparison of the ballistic curve was obtained numerically and was verified experimentally, and the failure patterns are presented using the optimal mesh densities which provide the stability of the results. A good agreement of the numerical and experimental results is observed.

Keywords: Aluminum alloy, ballistic behavior, failure criterion, numerical simulation.

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