Search results for: Dynamic Bayesian networks

Authors: R. Barbour

Abstract:

Peace-building organisations act as a network of information for communities. Through fieldwork, it was highlighted that grassroots organisations and activists may cooperate with each other in their actions of peace-building; however, they would not collaborate. Within two divided societies; Nicosia in Cyprus and Jerusalem in Israel, there is a distinction made by organisations and activists with regards to activities being more ‘co-operative’ than ‘collaborative’. This theme became apparent when having informal conversations and semi-structured interviews with various members of the activist communities. This idea needs further exploration as these distinctions could impact upon the efficiency of peacebuilding activities within divided societies. Civil societies within divided landscapes, both physically and socially, play an important role in conflict resolution. How organisations and activists interact with each other has the possibility to be very influential with regards to peacebuilding activities. Working together sets a positive example for divided communities. Cooperation may be considered a primary level of interaction between CSOs. Therefore, at the beginning of a working relationship, organisations cooperate over basic agendas, parallel power structures and focus, which led to the same objective. Over time, in some instances, due to varying factors such as funding, more trust and understanding within the relationship, it could be seen that processes progressed to more collaborative ways. It is evident to see that NGOs and activist groups are highly independent and focus on their own agendas before coming together over shared issues. At this time, there appears to be more collaboration in Nicosia among CSOs and activists than Jerusalem. The aims and objectives of agendas also influence how organisations work together. In recent years, Nicosia, and Cyprus in general, have perhaps changed their focus from peace-building initiatives to more environmental issues which have become new-age reconciliation topics. Civil society does not automatically indicate like-minded organisations however solidarity within social groups can create ties that bring people and resources together. In unequal societies, such as those in Nicosia and Jerusalem, it is these ties that cut across groups and are essential for social cohesion. Societies are a collection of social groups; individuals who have come together over common beliefs. These groups in turn shape the identities and determine the values and structures within societies. At many different levels and stages, social groups work together through cooperation and collaboration. These structures in turn have the capabilities to open up networks to less powerful or excluded groups, with the aim to produce social cohesion which may contribute social stability and economic welfare over any extended period.

Keywords: Collaboration, cooperation, grassroots activism, networks of communication.

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Authors: Mohamed Omar

Abstract:

Superelastic Shape Memory Alloy (SMA) is accepted when it used as connection in steel structures. The seismic behaviour of steel frames with SMA is being assessed in this study. Three eightstorey steel frames with different SMA systems are suggested, the first one of which is braced with diagonal bracing system, the second one is braced with nee bracing system while the last one is which the SMA is used as connection at the plastic hinge regions of beams. Nonlinear time history analyses of steel frames with SMA subjected to two different ground motion records have been performed using Seismostruct software. To evaluate the efficiency of suggested systems, the dynamic responses of the frames were compared. From the comparison results, it can be concluded that using SMA element is an effective way to improve the dynamic response of structures subjected to earthquake excitations. Implementing the SMA braces can lead to a reduction in residual roof displacement. The shape memory alloy is effective in reducing the maximum displacement at the frame top and it provides a large elastic deformation range. SMA connections are very effective in dissipating energy and reducing the total input energy of the whole frame under severe seismic ground motion. Using of the SMA connection system is more effective in controlling the reaction forces at the base frame than other bracing systems. Using SMA as bracing is more effective in reducing the displacements. The efficiency of SMA is dependant on the input wave motions and the construction system as well.

Keywords: Finite element analysis, seismic response, shapesmemory alloy, steel frame, superelasticity

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety.

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Authors: Indiramma M., K. R. Anandakumar

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Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Keywords: Collaborative Decision making, Trust, Multi Agent System (MAS), Bayesian Network, Reinforcement Learning.

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Authors: Justinian Anatory

Abstract:

power-line networks are promise infrastructure for broadband services provision to end users. However, the network performance is affected by stochastic channel changing which is due to load impedances, number of branches and branched line lengths. It has been proposed that multi-carrier modulations techniques such as orthogonal frequency division multiplexing (OFDM), Multi-Carrier Spread Spectrum (MC-SS), wavelet OFDM can be used in such environment. This paper investigates the performance of different indoor topologies of power-line networks that uses MC-SS modulation scheme.It is observed that when a branch is added in the link between sending and receiving end of an indoor channel an average of 2.5dB power loss is found. In additional, when the branch is added at a node an average of 1dB power loss is found. Additionally when the terminal impedances of the branch change from line characteristic impedance to impedance either higher or lower values the channel performances were tremendously improved. For example changing terminal load from characteristic impedance (85 .) to 5 . the signal to noise ratio (SNR) required to attain the same performances were decreased from 37dB to 24dB respectively. Also, changing the terminal load from channel characteristic impedance (85 .) to very higher impedance (1600 .) the SNR required to maintain the same performances were decreased from 37dB to 23dB. The result concludes that MC-SS performs better compared with OFDM techniques in all aspects and especially when the channel is terminated in either higher or lower impedances.

Keywords: Communication channel model; Broadband Powerlinecommunication; Branched network; OFDM; Delay Spread, MCSS;impulsive noise; load impedance

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: Data mining, digital libraries, digital preservation, file format.

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Authors: Junaid Kameran Ahmed

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A laminated plate composite of graphite/epoxy has been analyzed dynamically in the present work by using a quadratic element (8-node diso-parametric), and by depending on 1^st order shear deformation theory, every node in this element has 6-degrees of freedom (displacement in x, y, and z axis and twist about x, y, and z axis). The dynamic analysis in the present work covered parametric studies on a composite laminated plate (square plate) to determine its effect on the natural frequency of the plate. The parametric study is represented by set of changes (plate thickness, number of layers, support conditions, layer orientation), and the plates have been simulated by using ANSYS package 12. The boundary conditions considered in this study, at all four edges of the plate, are simply supported and fixed boundary condition. The results obtained from ANSYS program show that the natural frequency for both fixed and simply supported increases with increasing the number of layers, but this increase in the natural frequency for the first five modes will be neglected after 10 layers. And it is observed that the natural frequency of a composite laminated plate will change with the change of ply orientation, the natural frequency increases and it will be at maximum with angle 45 of ply for simply supported laminated plate, and maximum natural frequency will be with cross-ply (0/90) for fixed laminated composite plate. It is also observed that the natural frequency increase is approximately doubled when the thickness is doubled.

Keywords: Laminated plate, orthotropic plate, square plate, natural frequency, graphite/epoxy.

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices. 

Keywords: Industry 4.0., Mass Customization, Production networks, Virtual Process-Chain.

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Authors: Safyeh Soufian, Hoosein Naderi-Manesh, Abdoali Alizadeh, Mohammad Nabi Sarbolouki

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Aurein 1.2 is a 13-residue amphipathic peptide with antibacterial and anticancer activity. Aurein1.2 and its retro analog were synthesized to study the activity of the peptides in relation to their structure. The antibacterial test result showed the retro-analog is inactive. The secondary structural analysis by CD spectra indicated that both of the peptides at TFE/Water adopt alpha-helical conformation. MD simulation was performed on aurein 1.2 and retro-analog in water and TFE in order to analyse the factors that are involved in the activity difference between retro and the native peptide. The simulation results are discussed and validated in the light of experimental data from the CD experiment. Both of the peptides showed a relatively similar pattern for their hydrophobicity, hydrophilicity, solvent accessible surfaces, and solvent accessible hydrophobic surfaces. However, they showed different in directions of dipole moment of peptides. Also, Our results further indicate that the reversion of the amino acid sequence affects flexibility .The data also showed that factors causing structural rigidity may decrease the activity. Consequently, our finding suggests that in the case of sequence-reversed peptide strategy, one has to pay attention to the role of amino acid sequence order in making flexibility and role of dipole moment direction in peptide activity. KeywordsAntimicrobial peptides, retro, molecular dynamic, circular dichroism.

Keywords: Antimicrobial peptides, retro, molecular dynamic, circular dichroism.

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Authors: Emilia Nercissians

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Neoclassical and functionalist explanations of self organization in multiagent systems have been criticized on several accounts including unrealistic explication of overadapted agents and failure to resolve problems of externality. The paper outlines a more elaborate and dynamic model that is capable of resolving these dilemmas. An illustrative example where behavioral diversity is cobred in a repeated nonzero sum task via evolutionary computing is presented.

Keywords: evolutionary stability, externalities, neofunctionalism, prisoners' dilemma.

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Authors: Migbar Assefa

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The performance of a machine tool is eventually assessed by its ability to produce a component of the required geometry in minimum time and at small operating cost. It is customary to base the structural design of any machine tool primarily upon the requirements of static rigidity and minimum natural frequency of vibration. The operating properties of machines like cutting speed, feed and depth of cut as well as the size of the work piece also have to be kept in mind by a machine tool structural designer. This paper presents a novel approach to the design of machine tool column for static and dynamic rigidity requirement. Model evaluation is done effectively through use of General Finite Element Analysis software ANSYS. Studies on machine tool column are used to illustrate finite element based concept evaluation technique. This paper also presents results obtained from the computations of thin walled box type columns that are subjected to torsional and bending loads in case of static analysis and also results from modal analysis. The columns analyzed are square and rectangle based tapered open column, column with cover plate, horizontal partitions and with apertures. For the analysis purpose a total of 70 columns were analyzed for bending, torsional and modal analysis. In this study it is observed that the orientation and aspect ratio of apertures have no significant effect on the static and dynamic rigidity of the machine tool structure.

Keywords: Finite Element Modeling, Modal Analysis, Machine tool structure, Static Analysis.

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Authors: Ionel Stanculeanu, Theodor Borangiu

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This paper presents a new approach in the identification of the quadrotor dynamic model using a black-box system for identification. Also the paper considers the problems which appear during the identification in the closed-loop and offers a technical solution for overcoming the correlation between the input noise present in the output

Keywords: System identification, UAV, prediction error method, quadrotor.

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Authors: Seok Hong Min, Woo Young Jung, Tae Kwon Ha

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Superplastic deformation and high temperature load relaxation behavior of coarse-grained iron aluminides with the composition of Fe-28 at.% Al have been investigated. A series of load relaxation and tensile tests were conducted at temperatures ranging from 600 to 850oC. The flow curves obtained from load relaxation tests were found to have a sigmoidal shape and to exhibit stress vs. strain rate data in a very wide strain rate range from 10-7/s to 10-2/s. Tensile tests have been conducted at various initial strain rates ranging from 3×10-5/s to 1×10-2/s. Maximum elongation of ~500 % was obtained at the initial strain rate of 3×10-5/s and the maximum strain rate sensitivity was found to be 0.68 at 850oC in binary Fe-28Al alloy. Microstructure observation through the optical microscopy (OM) and the electron back-scattered diffraction (EBSD) technique has been carried out on the deformed specimens and it has revealed the evidences for grain boundary migration and grain refinement to occur during superplastic deformation, suggesting the dynamic recrystallization mechanism. The addition of Cr by the amount of 5 at.% appeared to deteriorate the superplasticity of the binary iron aluminide. By applying the internal variable theory of structural superplasticity, the addition of Cr has been revealed to lower the contribution of the frictional resistance to dislocation glide during high temperature deformation of the Fe3Al alloy.

Keywords: Iron aluminide (Fe3Al), large grain size, structural superplasticity, dynamic recrystallization, chromium (Cr).

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Authors: Jonghyun Park, Soonyoung Park, Sanggyun Kim, Wanhyun Cho, Sunworl Kim

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In general, image-based 3D scenes can now be found in many popular vision systems, computer games and virtual reality tours. So, It is important to segment ROI (region of interest) from input scenes as a preprocessing step for geometric stricture detection in 3D scene. In this paper, we propose a method for segmenting ROI based on tensor voting and Dirichlet process mixture model. In particular, to estimate geometric structure information for 3D scene from a single outdoor image, we apply the tensor voting and Dirichlet process mixture model to a image segmentation. The tensor voting is used based on the fact that homogeneous region in an image are usually close together on a smooth region and therefore the tokens corresponding to centers of these regions have high saliency values. The proposed approach is a novel nonparametric Bayesian segmentation method using Gaussian Dirichlet process mixture model to automatically segment various natural scenes. Finally, our method can label regions of the input image into coarse categories: “ground", “sky", and “vertical" for 3D application. The experimental results show that our method successfully segments coarse regions in many complex natural scene images for 3D.

Keywords: Region segmentation, tensor voting, image-based 3D, geometric structure, Gaussian Dirichlet process mixture model

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Authors: Waqed H. Almohammed, Mohammed Y. Fattah, Sajjad E. Rasheed

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Dynamic traffic loads cause deformation of underground pipes, resulting in vehicle discomfort. This makes it necessary to reinforce the layers of soil above underground pipes. In this study, the subbase layer was reinforced. Finite element software (PLAXIS 3D) was used to in the simulation, which includes geocell reinforcement, vehicle loading, soil layers and Glass Fiber Reinforced Plastic (GRP) pipe. Geocell reinforcement was modeled using a geogrid element, which was defined as a slender structure element that has the ability to withstand axial stresses but not to resist bending. Geogrids cannot withstand compression but they can withstand tensile forces. Comparisons have been made between the numerical models and experimental works, and a good agreement was obtained. Using the mathematical model, the performance of three different pipes of diameter 600 mm, 800 mm, and 1000 mm, and three different vehicular speeds of 20 km/h, 40 km/h, and 60 km/h, was examined to determine their impact on surface settlement and vertical pressure at the pipe crown for two cases: with and without geocell reinforcement. The results showed that, for a pipe diameter of 600 mm under geocell reinforcement, surface settlement decreases by 94 % when the speed of the vehicle is 20 km/h and by 98% when the speed of the vehicle is 60 km/h. Vertical pressure decreases by 81 % when the diameter of the pipe is 600 mm, while the value decreases to 58 % for a pipe with diameter 1000 mm. The results show that geocell reinforcement causes a significant and positive reduction in surface settlement and vertical stress above the pipe crown, leading to an increase in pipe safety.

Keywords: Dynamic loading, geocell reinforcement, GRP pipe, PLAXIS 3D, surface settlement.

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Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic.

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: Cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing.

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Authors: Nooshin La'l Mohamadi

Abstract:

Due to the fact that in the new century customers tend to express globally increasing demands, networks of interconnected businesses have been established in societies and the management of such networks seems to be a major key through gaining competitive advantages. Supply chain management encompasses such managerial activities. Within a supply chain, a critical role is played by quality. QFD is a widely-utilized tool which serves the purpose of not only bringing quality to the ultimate provision of products or service packages required by the end customer or the retailer, but it can also initiate us into a satisfactory relationship with our initial customer; that is the wholesaler. However, the wholesalers- cooperation is considerably based on the capabilities that are heavily dependent on their locations and existing circumstances. Therefore, it is undeniable that for all companies each wholesaler possesses a specific importance ratio which can heavily influence the figures calculated in the House of Quality in QFD. Moreover, due to the competitiveness of the marketplace today, it-s been widely recognized that consumers- expression of demands has been highly volatile in periods of production. Apparently, such instability and proneness to change has been very tangibly noticed and taking it into account during the analysis of HOQ is widely influential and doubtlessly required. For a more reliable outcome in such matters, this article demonstrates the application viability of Analytic Network Process for considering the wholesalers- reputation and simultaneously introduces a mortality coefficient for the reliability and stability of the consumers- expressed demands in course of time. Following to this, the paper provides further elaboration on the relevant contributory factors and approaches through the calculation of such coefficients. In the end, the article concludes that an empirical application is needed to achieve broader validity.

Keywords: Analytic Network Process, Quality Function Deployment, QFD flaws, Supply Chain Management

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Authors: Shahana T. K., Babita R. Jose, K. Poulose Jacob, Sreela Sasi

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The modern telecommunication industry demands higher capacity networks with high data rate. Orthogonal frequency division multiplexing (OFDM) is a promising technique for high data rate wireless communications at reasonable complexity in wireless channels. OFDM has been adopted for many types of wireless systems like wireless local area networks such as IEEE 802.11a, and digital audio/video broadcasting (DAB/DVB). The proposed research focuses on a concatenated coding scheme that improve the performance of OFDM based wireless communications. It uses a Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. Here, a direct conversion of analog signal to residue domain is done to reduce the conversion complexity using sigma-delta based parallel analog-to-residue converter. The bit error rate (BER) performances of the proposed system under different channel conditions are investigated. These include the effect of additive white Gaussian noise (AWGN), multipath delay spread, peak power clipping and frame start synchronization error. The simulation results show that the proposed RRNS-Convolutional concatenated coding (RCCC) scheme provides significant improvement in the system performance by exploiting the inherent properties of RRNS.

Keywords: Analog-to-residue converter, Concatenated codes, OFDM, Redundant Residue Number System, Sigma-delta modulator, Wireless communication

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

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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: Emin Z. Mahmud

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This paper presents the observations from a series of shaking-table tests done on a 1:1 scaled confined masonry wall model, with opening for a door – specimens CMDuS (confined masonry wall with opening for a door before strengthening) and CMDS (confined masonry wall with opening for a door after strengthening). Frequency and stiffness changes before and after GFRP (Glass Fiber Reinforced Plastic) wall strengthening are analyzed. Definition of dynamic properties of the models was the first step of the experimental testing, which enabled acquiring important information about the achieved stiffness (natural frequencies) of the model. The natural frequency was defined in the Y direction of the model by applying resonant frequency search tests. It is important to mention that both specimens CMDuS and CMDS are subjected to the same effects. The tests are realized in the laboratory of the Institute of Earthquake Engineering and Engineering Seismology (IZIIS), Skopje. The specimens were examined separately on the shaking table, with uniaxial, in-plane excitation. After testing, samples were strengthened with GFRP and re-tested. The initial frequency of the undamaged model CMDuS is 13.55 Hz, while at the end of the testing, the frequency decreased to 6.38 Hz. This emphasizes the reduction of the initial stiffness of the model due to damage, especially in the masonry and tie-beam to tie-column connection. After strengthening of the damaged wall, the natural frequency increases to 10.89 Hz. This highlights the beneficial effect of the strengthening. After completion of dynamic testing at CMDS, the natural frequency is reduced to 6.66 Hz.

Keywords: Behavior of masonry structures, Eurocode, fundamental frequency, masonry, shaking table test, strengthening.

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of acquiring new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used in this work is to analyze the dynamics of different brain areas during a cognitive activity to find the relationships between the other areas analyzed to understand the functioning of neural networks better. Also, the latest advances in neuroscience have revealed the exis-tence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neurodevelopmental difficulties for their subsequent assessment and therapy. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process, specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho-pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, learning disabilities, neural networks

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Authors: A. M. Alaskari, S. E. Oraby

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The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.

Keywords: Dynamic force signals, surface roughness (finish), tool wear and deformation, tool wear modes (nose, flank)

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Authors: Yi-Feng Su, Chia-Tseng Chen, Hsueh-Lung Liao

Abstract:

The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.

Keywords: Lane mark detection, lane departure warning (LDW), dynamic range of interesting (DROI), forward collision warning (FCW), adaptive front-lighting system (AFS).

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Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

Abstract:

The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them based on a couple of related works. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs) are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The current challenges of various architectures are discussed in detail, with the major issue identified as obstruction of communication paths by buildings, trees, hills, etc.

Keywords: Communication technologies, environmental monitoring, Internet of Things, IoT, IoT deployment challenges.

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Authors: S. Bouhouche, M. Lahreche, S. Ziani, J. Bast

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Modern manufacturing facilities are large scale, highly complex, and operate with large number of variables under closed loop control. Early and accurate fault detection and diagnosis for these plants can minimise down time, increase the safety of plant operations, and reduce manufacturing costs. Fault detection and isolation is more complex particularly in the case of the faulty analog control systems. Analog control systems are not equipped with monitoring function where the process parameters are continually visualised. In this situation, It is very difficult to find the relationship between the fault importance and its consequences on the product failure. We consider in this paper an approach to fault detection and analysis of its effect on the production quality using an adaptive centring and scaling in the pickling process in cold rolling. The fault appeared on one of the power unit driving a rotary machine, this machine can not track a reference speed given by another machine. The length of metal loop is then in continuous oscillation, this affects the product quality. Using a computerised data acquisition system, the main machine parameters have been monitored. The fault has been detected and isolated on basis of analysis of monitored data. Normal and faulty situation have been obtained by an artificial neural network (ANN) model which is implemented to simulate the normal and faulty status of rotary machine. Correlation between the product quality defined by an index and the residual is used to quality classification.

Keywords: Modeling, fault detection and diagnosis, parameters estimation, neural networks, Fault Detection and Diagnosis (FDD), pickling process.

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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Authors: Chapman Eze Nnadozie

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Cloud computing, a technology that is made possible through virtualization within networks represents a shift from the traditional ownership of infrastructure and other resources by distinct organization to a more scalable pattern in which computer resources are rented online to organizations on either as a pay-as-you-use basis or by subscription. In other words, cloud computing entails the renting of computing resources (such as storage space, memory, servers, applications, networks, etc.) by a third party to its clients on a pay-as-go basis. It is a new innovative technology that is globally embraced because of its renowned benefits, profound of which is its cost effectiveness on the part of organizations engaged with its services. In Nigeria, the services are provided either directly to companies mostly by the key IT players such as Microsoft, IBM, and Google; or in partnership with some other players such as Infoware, Descasio, and Sunnet. This action enables organizations to rent IT resources on a pay-as-you-go basis thereby salvaging them from wastages accruable on acquisition and maintenance of IT resources such as ownership of a separate data centre. This paper intends to appraise the challenges of cloud computing adoption in Nigeria, bearing in mind the country’s peculiarities’ in terms of infrastructural development. The methodologies used in this paper include the use of research questionnaires, formulated hypothesis, and the testing of the formulated hypothesis. The major findings of this paper include the fact that there are some addressable challenges to the adoption of cloud computing in Nigeria. Furthermore, the country will gain significantly if the challenges especially in the area of infrastructural development are well addressed. This is because the research established the fact that there are significant gains derivable by the adoption of cloud computing by organizations in Nigeria. However, these challenges can be overturned by concerted efforts in the part of government and other stakeholders.

Keywords: Cloud computing, data centre, infrastructure, IT resources, network, servers, virtualization.

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Authors: Karamitsos Ioannis, Orfanidis Konstantinos

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In this paper an analysis of blackouts in electric power transmission systems is implemented using a model and studied in simple networks with a regular topology. The proposed model describes load demand and network improvements evolving on a slow timescale as well as the fast dynamics of cascading overloads and outages.

Keywords: Blackout, Generator, Load, Power Load.

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Authors: Kamal K.Bharadwaj, Rekha Kandwal

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An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.

Keywords: Cumulative learning, clustering, data mining, hierarchical production rules.

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