Search results for: adaptive differentiators
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 988

Search results for: adaptive differentiators

508 Chaotic Control, Masking and Secure Communication Approach of Supply Chain Attractor

Authors: Unal Atakan Kahraman, Yilmaz Uyaroğlu

Abstract:

The chaotic signals generated by chaotic systems have some properties such as randomness, complexity and sensitive dependence on initial conditions, which make them particularly suitable for secure communications. Since the 1990s, the problem of secure communication, based on chaos synchronization, has been thoroughly investigated and many methods, for instance, robust and adaptive control approaches, have been proposed to realize the chaos synchronization. In this paper, an improved secure communication model is proposed based on control of supply chain management system. Control and masking communication simulation results are used to visualize the effectiveness of chaotic supply chain system also performed on the application of secure communication to the chaotic system. So, we discover the secure phenomenon of chaos-amplification in supply chain system

Keywords: chaotic analyze, control, secure communication, supply chain attractor

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507 Traditional Uses of Medicinal Plants in Albania: Historical and Theoretical Considerations

Authors: Ani Bajrami

Abstract:

The birth of traditional medicine is related to plant diversity in a region, and the knowledge regarding them has been used and culturally transmitted over generations by members of a certain society. In this context, Traditional Ecological Knowledge (TEK) concerning the use of plants for medicinal purposes had survival value and was adaptive for people living in different habitats around the world. Albanian flora has a high considerably number of medicinal plants, and they have been extensively used albeit expressed in folk medicinal knowledge and practices. Over the past decades, a number of ethnobotanical studies and extensive fieldwork has been conducted in Albania both by local and foreign scientists. In addition, ethnobotany is experiencing a theoretical and conceptual diversification. This article is a historical review of ethnobotanical studies conducted in Albania after the Second World War and provides theoretical considerations on how these studies should be conducted in the future.

Keywords: medicinal plants, traditional ecological knowledge, historical ethnobotany, theory, albania

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506 FPGA Implementation of Adaptive Clock Recovery for TDMoIP Systems

Authors: Semih Demir, Anil Celebi

Abstract:

Circuit switched networks widely used until the end of the 20th century have been transformed into packages switched networks. Time Division Multiplexing over Internet Protocol (TDMoIP) is a system that enables Time Division Multiplexing (TDM) traffic to be carried over packet switched networks (PSN). In TDMoIP systems, devices that send TDM data to the PSN and receive it from the network must operate with the same clock frequency. In this study, it was aimed to implement clock synchronization process in Field Programmable Gate Array (FPGA) chips using time information attached to the packages received from PSN. The designed hardware is verified using the datasets obtained for the different carrier types and comparing the results with the software model. Field tests are also performed by using the real time TDMoIP system.

Keywords: clock recovery on TDMoIP, FPGA, MATLAB reference model, clock synchronization

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505 Black Box Model and Evolutionary Fuzzy Control Methods of Coupled-Tank System

Authors: S. Yaman, S. Rostami

Abstract:

In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability.

Keywords: function tuner method (FTM), fuzzy modeling, fuzzy PID controller, genetic algorithm (GA)

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504 Transformable Lightweight Structures for Short-term Stay

Authors: Anna Daskalaki, Andreas Ashikalis

Abstract:

This is a conceptual project that suggests an alternative type of summer camp in the forest of Rouvas in the island of Crete. Taking into account some feasts that are organised by the locals or mountaineering clubs near the church of St. John, we created a network of lightweight timber structures that serve the needs of the visitor. These structures are transformable and satisfy the need for rest, food, and sleep – this means a seat, a table and a tent are embodied in each structure. These structures blend in with the environment as they are being installed according to the following parameters: (a) the local relief, (b) the clusters of trees, and (c) the existing paths. Each timber structure could be considered as a module that could be totally independent or part of a bigger construction. The design showcases the advantages of a timber structure as it can be quite adaptive to the needs of the project, but also it is a sustainable and environmentally friendly material that can be recycled. Finally, it is important to note that the basic goal of this project is the minimum alteration of the natural environment.

Keywords: lightweight structures, timber, transformable, tent

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503 Investigating Re-Use a Historical Masonry Arch Bridge

Authors: H. A. Erdogan

Abstract:

Historical masonry arch bridges built centuries ago have fulfilled their function until recent decades. However, from the beginning of 20th century, these bridges have remained inadequate as a result of increasing speed, size and capacity of the means of transport. Although new bridges have been built in many places, masonry bridges located within the city limits still need to be used. When the size and transportation loads of modern vehicles are taken into account, it is apparent that historical masonry arch bridges would be exposed to greater loads than their initial design loads. Because of that, many precautions taken either remain insufficient or damage these bridges. In this study, the history of Debbaglar Bridge, one of the historic bridges located in the city center of Aksaray/Turkey is presented and its existing condition is evaluated. Structural analysis of the bridge under present conditions and loads is explained. Moreover, the retrofit and restoration application prepared considering the analysis data is described.

Keywords: adaptive re-use, Aksaray debbaglar bridge, masonry bridge, reconstruction

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502 Fuzzy-Sliding Controller Design for Induction Motor Control

Authors: M. Bouferhane, A. Boukhebza, L. Hatab

Abstract:

In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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501 The University of California at Los Angeles-Young Autism Project: A Systematic Review of Replication Studies

Authors: Michael Nicolosi, Karola Dillenburger

Abstract:

The University of California at Los Angeles-Young Autism Project (UCLA-YAP) provides one of the best-known and most researched comprehensive applied behavior analysis-based intervention models for young children on the autism spectrum. This paper reports a systematic literature review of replication studies over more than 30 years. The data show that the relatively high-intensity UCLA-YAP model can be greatly beneficial for children on the autism spectrum, particularly with regard to their cognitive functioning and adaptive behavior. This review concludes that, while more research is always welcome, the impact of the UCLA-YAP model on autism interventions is justified by more than 30 years of outcome evidence.

Keywords: ABA, applied behavior analysis, autism, California at Los Angeles Young Autism project, intervention, Lovaas, UCLA-YAP

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500 Rule Insertion Technique for Dynamic Cell Structure Neural Network

Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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499 Color Image Enhancement Using Multiscale Retinex and Image Fusion Techniques

Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

Abstract:

In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

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498 Application of Adaptive Neural Network Algorithms for Determination of Salt Composition of Waters Using Laser Spectroscopy

Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

Abstract:

In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: inverse problems, multi-component solutions, neural networks, Raman spectroscopy

Procedia PDF Downloads 499
497 Use of Artificial Intelligence Based Models to Estimate the Use of a Spectral Band in Cognitive Radio

Authors: Danilo López, Edwin Rivas, Fernando Pedraza

Abstract:

Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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496 Relationship and Comorbidity between Down Syndrome and Autism Spectrum Disorder

Authors: Elena Jiménez Lidueña, Noelia Santos Muriel, Patricia López Resa, Noelia Pulido García, Esther Moraleda Sepúlveda

Abstract:

In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profiles. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder and, on the other hand, shows a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: Down Syndrome, Autism, comorbidity, linguistic

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495 Task Space Synchronization Control of Multi-Robot Arms with Position Synchronous Method

Authors: Zijian Zhang, Yangyang Dong

Abstract:

Synchronization is of great importance to ensure the multi-arm robot to complete the task. Therefore, a synchronous controller is designed to coordinate task space motion of the multi-arm in the paper. The position error, the synchronous position error, and the coupling position error are all considered in the controller. Besides, an adaptive control method is used to adjust parameters of the controller to improve the effectiveness of coordinated control performance. Simulation in the Matlab shows the effectiveness of the method. At last, a robot experiment platform with two 7-DOF (Degree of Freedom) robot arms has been established and the synchronous controller simplified to control dual-arm robot has been validated on the experimental set-up. Experiment results show the position error decreased 10% and the corresponding frequency is also greatly improved.

Keywords: synchronous control, space robot, task space control, multi-arm robot

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494 Employers’ Perspective on Female Graduate Employability in Nigeria

Authors: Temitope Faloye

Abstract:

In today’s changing job market economy, most employers of labor want employees who are employable and possess relevant skills. Graduates need to possess generic skills due to the continually changing nature of the job market, which requires adaptive coping strategies. Most employers of labor complain that graduates are not employable, which is one of the major factors causing a high rate of graduate unemployment in Nigeria. However, the number of unemployed females is higher than that of unemployed males; hence gender difference is linked to the employability of graduates. The human capital theory is considered an appropriate theory for this study. A qualitative approach will be used to provide answers to the research questions. Therefore, the research study aims to investigate the employers’ perspective on female graduate employability in Nigeria.

Keywords: graduate employability, generic skills, graduate unemployment, gender

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493 Major Histocompatibility Complex (MHC) Polymorphism and Disease Resistance

Authors: Oya Bulut, Oguzhan Avci, Zafer Bulut, Atilla Simsek

Abstract:

Livestock breeders have focused on the improvement of production traits with little or no attention for improvement of disease resistance traits. In order to determine the association between the genetic structure of the individual gene loci with possibility of the occurrence and the development of diseases, MHC (major histocompatibility complex) are frequently used. Because of their importance in the immune system, MHC locus is considered as candidate genes for resistance/susceptibility against to different diseases. Major histocompatibility complex (MHC) molecules play a critical role in both innate and adaptive immunity and have been considered candidate molecular markers of an association between polymorphisms and resistance/susceptibility to diseases. The purpose of this study is to give some information about MHC genes become an important area of study in recent years in terms of animal husbandry and determine the relation between MHC genes and resistance/susceptibility to disease.

Keywords: MHC, polymorphism, disease, resistance

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492 Real-Time Adaptive Obstacle Avoidance with DS Method and the Influence of Dynamic Environments Change on Different DS

Authors: Saeed Mahjoub Moghadas, Farhad Asadi, Shahed Torkamandi, Hassan Moradi, Mahmood Purgamshidian

Abstract:

In this paper, we present real-time obstacle avoidance approach for both autonomous and non-autonomous DS-based controllers and also based on dynamical systems (DS) method. In this approach, we can modulate the original dynamics of the controller and it allows us to determine safety margin and different types of DS to increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle and especially when robot moves very fast in changeable complex environments. The method is validated in simulation and influence of different autonomous and non-autonomous DS such as limit cycles, and unstable DS on this algorithm and also the position of different obstacles in complex environment is explained. Finally, we describe how the avoidance trajectories can be verified through different parameters such as safety factor.

Keywords: limit cycles, nonlinear dynamical system, real time obstacle avoidance, DS-based controllers

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491 Unsupervised Assistive and Adaptive Intelligent Agent in Smart Environment

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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490 Alwadei Syndrome - A Genetic Cause Of Intellectual Disability

Authors: Mafalda Moreira, Diana Alba, Inês Paiva Ferreira, Rita Calejo, Ana Rita Soares, Leonilde Machado

Abstract:

Intellectual disability (ID) is characterized by deficits in intellectualfunctioningassociatedwithalterations in the adaptive behaviour, whose onset is inthedevelopmentalperiod. Itaffects 3% of the population, ofwhich 10% have a geneticaetiology. One of those causes isAlwadeiSyndrome, with 3 cases describedworldwide. It results from a homozygous nonsense mutation in theRUSC2 gene andisassociatedwithintellectualdisabilityanddysmorphic facialfeatures. Theauthorsreportthe case of a 5-year-old-boy, born to a healthymotherafter a full-termuneventfulpregnancy, thatwasreferred to Neurodevelopmentalconsultationdue toglobal developmentaldelay. Familyhistoryrevealedlearningdifficulties in the paternal brotherhood. Milddismorphicfeatureswereevidentsuch as darkinfraorbitalregion, low-set ears, beakednose, retrognathism, high-archedpalateandjointhyperlaxity. WechslerIntelligenceScale for Children III fullscaleIQ quoted 61. Karyotypeandchromosomalmicroarrayanalysiswerenormal, as well as the fragile X molecular study. DNA sequencingwasthenperformedandallowedtheidentificationof amutation in the RUSC2 gene. Theetiologicaldiagnosisof ID remains unknown in up to 80% of cases, creatinguncertainty in children’sfamilies. Theadvances in DNA sequencingtechnologieshaveincreasedourknowledgeofthegeneticdiseasesinvolved, as theAlwadeisyndromewasonlydescribedsince 2016. Thegeneticdiagnosisof ID allowsfamilygeneticcounselingandenablesthedevelopmentof target therapeutic approaches.

Keywords: intellectual disability, genetic aetiology, alwadei syndrome, RUSC2

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489 Home Legacy Device Output Estimation Using Temperature and Humidity Information by Adaptive Neural Fuzzy Inference System

Authors: Sung Hyun Yoo, In Hwan Choi, Jun Ho Jung, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Home energy management system (HEMS) has been issued to reduce the power consumption. The HEMS performs electric power control for the indoor electric device. However, HEMS commonly treats the smart devices. In this paper, we suggest the output estimation of home legacy device using the artificial neural fuzzy inference system (ANFIS). This paper discusses the overview and the architecture of the system. In addition, accurate performance of the output estimation using the ANFIS inference system is shown via a numerical example.

Keywords: artificial neural fuzzy inference system (ANFIS), home energy management system (HEMS), smart device, legacy device

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488 Comparison of ANFIS Update Methods Using Genetic Algorithm, Particle Swarm Optimization, and Artificial Bee Colony

Authors: Michael R. Phangtriastu, Herriyandi Herriyandi, Diaz D. Santika

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This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set.

Keywords: ANFIS, artificial bee colony, genetic algorithm, metaheuristic algorithm, particle swarm optimization

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487 Numerical Modelling of Effective Diffusivity in Bone Tissue Engineering

Authors: Ayesha Sohail, Khadija Maqbool, Anila Asif, Haroon Ahmad

Abstract:

The field of tissue engineering is an active area of research. Bone tissue engineering helps to resolve the clinical problems of critical size and non-healing defects by the creation of man-made bone tissue. We will design and validate an efficient numerical model, which will simulate the effective diffusivity in bone tissue engineering. Our numerical model will be based on the finite element analysis of the diffusion-reaction equations. It will have the ability to optimize the diffusivity, even at multi-scale, with the variation of time. It will also have a special feature, with which we will not only be able to predict the oxygen, glucose and cell density dynamics, more accurately, but will also sort the issues arising due to anisotropy. We will fix these problems with the help of modifying the governing equations, by selecting appropriate spatio-temporal finite element schemes, by adaptive grid refinement strategy and by transient analysis.

Keywords: scaffolds, porosity, diffusion, transient analysis

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486 State and Benefit: Delivering the First State of the Bays Report for Victoria

Authors: Scott Rawlings

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Victoria’s first State of the Bays report is an historic baseline study of the health of Port Phillip Bay and Western Port. The report includes 50 assessments of 36 indicators across a broad array of topics from the nitrogen cycle and water quality to key marine species and habitats. This paper discusses the processes for determining and assessing the indicators and comments on future priorities identified to maintain and improve the health of these water ways. Victoria’s population is now at six million, and growing at a rate of over 100,000 people per year - the highest increase in Australia – and the population of greater Melbourne is over four million. Port Phillip Bay and Western Port are vital marine assets at the centre of this growth and will require adaptive strategies if they are to remain in good condition and continue to deliver environmental, economic and social benefits. In 2014, it was in recognition of these pressures that the incoming Victorian Government committed to reporting on the state of the bays every five years. The inaugural State of the Bays report was issued by the independent Victorian Commissioner for Environmental Sustainability. The report brought together what is known about both bays, based on existing research. It was a baseline on which future reports will build and, over time, include more of Victoria’s marine environment. Port Phillip Bay and Western Port generally demonstrate healthy systems. Specific threats linked to population growth are a significant pressure. Impacts are more significant where human activity is more intense and where nutrients are transported to the bays around the mouths of creeks and drainage systems. The transport of high loads of nutrients and pollutants to the bays from peak rainfall events is likely to increase with climate change – as will sea level rise. Marine pests are also a threat. More than 100 introduced marine species have become established in Port Phillip Bay and can compete with native species, alter habitat, reduce important fish stocks and potentially disrupt nitrogen cycling processes. This study confirmed that our data collection regime is better within the Marine Protected Areas of Port Phillip Bay than in other parts. The State of the Bays report is a positive and practical example of what can be achieved through collaboration and cooperation between environmental reporters, Government agencies, academic institutions, data custodians, and NGOs. The State of the Bays 2016 provides an important foundation by identifying knowledge gaps and research priorities for future studies and reports on the bays. It builds a strong evidence base to effectively manage the bays and support an adaptive management framework. The Report proposes a set of indicators for future reporting that will support a step-change in our approach to monitoring and managing the bays – a shift from reporting only on what we do know, to reporting on what we need to know.

Keywords: coastal science, marine science, Port Phillip Bay, state of the environment, Western Port

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485 Energy Recovery from Swell with a Height Inferior to 1.5 m

Authors: A. Errasti, F. Doffagne, O. Foucrier, S. Kao, A. Meigne, H. Pellae, T. Rouland

Abstract:

Renewable energy recovery is an important domain of research in past few years in view of protection of our ecosystem. Several industrial companies are setting up widespread recovery systems to exploit wave energy. Most of them have a large size, are implanted near the shores and exploit current flows. However, as oceans represent 70% of Earth surface, a huge space is still unexploited to produce energy. Present analysis focuses on surface small scale wave energy recovery. The principle is exactly the opposite of wheel damper for a car on a road. Instead of maintaining the car body as non-oscillatory as possible by adapted control, a system is designed so that its oscillation amplitude under wave action will be maximized with respect to a boat carrying it in view of differential potential energy recuperation. From parametric analysis of system equations, interesting domains have been selected and expected energy output has been evaluated.

Keywords: small scale wave, potential energy, optimized energy recovery, auto-adaptive system

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484 Exploring SSD Suitable Allocation Schemes Incompliance with Workload Patterns

Authors: Jae Young Park, Hwansu Jung, Jong Tae Kim

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Whether the data has been well parallelized is an important factor in the Solid-State-Drive (SSD) performance. SSD parallelization is affected by allocation scheme and it is directly connected to SSD performance. There are dynamic allocation and static allocation in representative allocation schemes. Dynamic allocation is more adaptive in exploiting write operation parallelism, while static allocation is better in read operation parallelism. Therefore, it is hard to select the appropriate allocation scheme when the workload is mixed read and write operations. We simulated conditions on a few mixed data patterns and analyzed the results to help the right choice for better performance. As the results, if data arrival interval is long enough prior operations to be finished and continuous read intensive data environment static allocation is more suitable. Dynamic allocation performs the best on write performance and random data patterns.

Keywords: dynamic allocation, NAND flash based SSD, SSD parallelism, static allocation

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483 Modeling and Simulation of Flow Shop Scheduling Problem through Petri Net Tools

Authors: Joselito Medina Marin, Norberto Hernández Romero, Juan Carlos Seck Tuoh Mora, Erick S. Martinez Gomez

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The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.

Keywords: flow-shop scheduling problem, makespan, Petri nets, state equation

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482 Evaluation and Selection of SaaS Product Based on User Preferences

Authors: Boussoualim Nacira, Aklouf Youcef

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Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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481 Modern Machine Learning Conniptions for Automatic Speech Recognition

Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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480 Robust Diagnosis of an Electro-Mechanical Actuators, Bond Graph LFT Approach

Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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479 Real-Time Episodic Memory Construction for Optimal Action Selection in Cognitive Robotics

Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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