Search results for: Fuzzy genetic network programming
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4536

Search results for: Fuzzy genetic network programming

876 Propagation Model for a Mass-Mailing Worm with Mailing List

Authors: Akira Kanaoka, Eiji Okamoto

Abstract:

Mass-mail type worms have threatened to become a large problem for the Internet. Although many researchers have analyzed such worms, there are few studies that consider worm propagation via mailing lists. In this paper, we present a mass-mailing type worm propagation model including the mailing list effect on the propagation. We study its propagation by simulation with a real e¬mail social network model. We show that the impact of the mailing list on the mass-mail worm propagation is significant, even if the mailing list is not large.

Keywords: Malware, simulation, complex networks

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875 Neuro-Hybrid Models for Automotive System Identification

Authors: Ventura Assuncao

Abstract:

In automotive systems almost all steps concerning the calibration of several control systems, e.g., low idle governor or boost pressure governor, are made with the vehicle because the timeto- production and cost requirements on the projects do not allow for the vehicle analysis necessary to build reliable models. Here is presented a procedure using parametric and NN (neural network) models that enables the generation of vehicle system models based on normal ECU engine control unit) vehicle measurements. These models are locally valid and permit pre and follow-up calibrations so that, only the final calibrations have to be done with the vehicle.

Keywords: Automotive systems, neuro-hybrid models, demodulator, nonlinear systems, identification, and neural networks.

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874 Bounds on Reliability of Parallel Computer Interconnection Systems

Authors: Ranjan Kumar Dash, Chita Ranjan Tripathy

Abstract:

The evaluation of residual reliability of large sized parallel computer interconnection systems is not practicable with the existing methods. Under such conditions, one must go for approximation techniques which provide the upper bound and lower bound on this reliability. In this context, a new approximation method for providing bounds on residual reliability is proposed here. The proposed method is well supported by two algorithms for simulation purpose. The bounds on residual reliability of three different categories of interconnection topologies are efficiently found by using the proposed method

Keywords: Parallel computer network, reliability, probabilisticgraph, interconnection networks.

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873 Regional Medical Imaging System

Authors: Michal Javornik, Otto Dostal, Karel Slavicek

Abstract:

The purpose of this article is to introduce an advanced system for the support of processing of medical image information, and the terminology related to this system, which can be an important element to a faster transition to a fully digitalized hospital. The core of the system is a set of DICOM compliant applications running over a dedicated computer network. The whole integrated system creates a collaborative platform supporting daily routines in the radiology community, developing communication channels, supporting the exchange of information and special consultations among various medical institutions as well as supporting medical training for practicing radiologists and medical students. It gives the users outside of hospitals the tools to work in almost the same conditions as in the radiology departments.

Keywords: DICOM, Integration, Medical Education, MedicalImaging

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872 Evaluating Performance of Quality-of-Service Routing in Large Networks

Authors: V. Narasimha Raghavan, M. Venkatesh, T. Peer Meera Labbai, Praveen Dwarakanath Prabhu

Abstract:

The performance and complexity of QoS routing depends on the complex interaction between a large set of parameters. This paper investigated the scaling properties of source-directed link-state routing in large core networks. The simulation results show that the routing algorithm, network topology, and link cost function each have a significant impact on the probability of successfully routing new connections. The experiments confirm and extend the findings of other studies, and also lend new insight designing efficient quality-of-service routing policies in large networks.

Keywords: QoS, Link-State Routing, Dijkstra, Path Selection, Path Computation.

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871 Analysis of Long-Term File System Activities on Cluster Systems

Authors: Hyeyoung Cho, Sungho Kim, Sik Lee

Abstract:

I/O workload is a critical and important factor to analyze I/O pattern and to maximize file system performance. However to measure I/O workload on running distributed parallel file system is non-trivial due to collection overhead and large volume of data. In this paper, we measured and analyzed file system activities on two large-scale cluster systems which had TFlops level high performance computation resources. By comparing file system activities of 2009 with those of 2006, we analyzed the change of I/O workloads by the development of system performance and high-speed network technology.

Keywords: I/O workload, Lustre, GPFS, Cluster File System

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870 Cloning and Functional Characterization of Promoter Elements of the D Hordein Gene from the Barley (Hordeum vulgare L.) by Bioinformatic Tools

Authors: Kobra Nalbandi, Bahram Baghban Kohnehrouz, Khalil Alami Saeed

Abstract:

The low level of foreign genes expression in transgenic plants is a key factor that limits plant genetic engineering. Because of the critical regulatory activity of the promoters on gene transcription, they are studied extensively to improve the efficiency of the plant transgenic system. The strong constitutive promoters, such as CaMV 35S promoter and Ubiqutin 1 maize are usually used in plant biotechnology research. However the expression level of the foreign genes in all tissues is often undesirable. But using a strong seed-specific promoter to limit gene expression in the seed solves such problems. The purpose of this study is to isolate one of the seed specific promoters of Hordeum vulgare. So one of the common varieties of Hordeum vulgare in Iran was selected and their genomes extracted then the D-Hordein promoter amplified using the specific designed primers. Then the amplified fragment of the insert cloned in an appropriate vector and then transformed to E. coli. At last for the final admission of accuracy the cloned fragments sent for sequencing. Sequencing analysis showed that the cloned fragment DHPcontained motifs; like TATA box, CAAT-box, CCGTCC-box, AMYBOX1 and E-box etc., which constituted the seed-specific promoter activity. The results were compared with sequences existing in data banks. D-Hordein promoters of Alger has 99% similarity at 100 % coverage. The results also showed that D-Hordein promoter of barley and HMW promoter of wheat are too similar.

Keywords: Barley, Seed specific promoter, Hordein.

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869 Validation Testing for Temporal Neural Networks for RBF Recognition

Authors: Khaled E. A. Negm

Abstract:

A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the relevant information in the neurons' delays. One of the fundamental findings of the this research also is that when using overlapping receptive fields to encode the data patterns it increases the network-s clustering capacity. The clustering algorithm that is discussed here is interesting from computer science and neuroscience point of view as well as from a perspective.

Keywords: Temporal Neurons, RBF Recognition, Perturbation, On Line Recognition.

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868 Evaluation of Model-Based Code Generation for Embedded Systems–Mature Approach for Development in Evolution

Authors: Nikolay P. Brayanov, Anna V. Stoynova

Abstract:

Model-based development approach is gaining more support and acceptance. Its higher abstraction level brings simplification of systems’ description that allows domain experts to do their best without particular knowledge in programming. The different levels of simulation support the rapid prototyping, verifying and validating the product even before it exists physically. Nowadays model-based approach is beneficial for modelling of complex embedded systems as well as a generation of code for many different hardware platforms. Moreover, it is possible to be applied in safety-relevant industries like automotive, which brings extra automation of the expensive device certification process and especially in the software qualification. Using it, some companies report about cost savings and quality improvements, but there are others claiming no major changes or even about cost increases. This publication demonstrates the level of maturity and autonomy of model-based approach for code generation. It is based on a real live automotive seat heater (ASH) module, developed using The Mathworks, Inc. tools. The model, created with Simulink, Stateflow and Matlab is used for automatic generation of C code with Embedded Coder. To prove the maturity of the process, Code generation advisor is used for automatic configuration. All additional configuration parameters are set to auto, when applicable, leaving the generation process to function autonomously. As a result of the investigation, the publication compares the quality of generated embedded code and a manually developed one. The measurements show that generally, the code generated by automatic approach is not worse than the manual one. A deeper analysis of the technical parameters enumerates the disadvantages, part of them identified as topics for our future work.

Keywords: Embedded code generation, embedded C code quality, embedded systems, model-based development.

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867 A Case Study on Optimization of Contractor’s Financing through Allocation of Subcontractors

Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

Abstract:

In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: Cash flow optimization, payment plan, procurement management, subcontracting plan.

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866 Application of Artificial Neural Networks for Temperature Forecasting

Authors: Mohsen Hayati, Zahra Mohebi

Abstract:

In this paper, the application of neural networks to study the design of short-term temperature forecasting (STTF) Systems for Kermanshah city, west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STTF systems is used. Our study based on MLP was trained and tested using ten years (1996-2006) meteorological data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STTF systems.

Keywords: Artificial neural networks, Forecasting, Weather, Multi-layer perceptron.

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865 Exponential Stability Analysis for Switched Cellular Neural Networks with Time-varying Delays and Impulsive Effects

Authors: Zixin Liu, Fangwei Chen

Abstract:

In this Letter, a class of impulsive switched cellular neural networks with time-varying delays is investigated. At the same time, parametric uncertainties assumed to be norm bounded are considered. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions guaranteeing exponential stability for all admissible parametric uncertainties are derived via constructing appropriate Lyapunov functional. One numerical example is provided to illustrate the validity of the main results obtained in this paper.

Keywords: Switched systems, exponential stability, cellular neural networks.

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864 Finding Equilibrium in Transport Networks by Simulation and Investigation of Behaviors

Authors: Gábor Szűcs, Gyula Sallai

Abstract:

The goal of this paper is to find Wardrop equilibrium in transport networks at case of uncertainty situations, where the uncertainty comes from lack of information. We use simulation tool to find the equilibrium, which gives only approximate solution, but this is sufficient for large networks as well. In order to take the uncertainty into account we have developed an interval-based procedure for finding the paths with minimal cost using the Dempster-Shafer theory. Furthermore we have investigated the users- behaviors using game theory approach, because their path choices influence the costs of the other users- paths.

Keywords: Dempster-Shafer theory, S-O and U-Otransportation network, uncertainty of information, Wardropequilibrium.

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863 Hardware Implementations for the ISO/IEC 18033-4:2005 Standard for Stream Ciphers

Authors: Paris Kitsos

Abstract:

In this paper the FPGA implementations for four stream ciphers are presented. The two stream ciphers, MUGI and SNOW 2.0 are recently adopted by the International Organization for Standardization ISO/IEC 18033-4:2005 standard. The other two stream ciphers, MICKEY 128 and TRIVIUM have been submitted and are under consideration for the eSTREAM, the ECRYPT (European Network of Excellence for Cryptology) Stream Cipher project. All ciphers were coded using VHDL language. For the hardware implementation, an FPGA device was used. The proposed implementations achieve throughputs range from 166 Mbps for MICKEY 128 to 6080 Mbps for MUGI.

Keywords: Cryptography, ISO/IEC 18033-4:2005 standard, Hardware implementation, Stream ciphers

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862 Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform

Authors: Hiram I. Beltrán, Arturo Rojo-Domínguez, Máximo Eduardo Sánchez Gutiérrez, Pedro Pablo González Pérez

Abstract:

A computational platform is presented in this contribution. It has been designed as a virtual laboratory to be used for exploring optimization algorithms in biological problems. This platform is built on a blackboard-based agent architecture. As a test case, the version of the platform presented here is devoted to the study of protein folding, initially with a bead-like description of the chain and with the widely used model of hydrophobic and polar residues (HP model). Some details of the platform design are presented along with its capabilities and also are revised some explorations of the protein folding problems with different types of discrete space. It is also shown the capability of the platform to incorporate specific tools for the structural analysis of the runs in order to understand and improve the optimization process. Accordingly, the results obtained demonstrate that the ensemble of computational tools into a single platform is worthwhile by itself, since experiments developed on it can be designed to fulfill different levels of information in a self-consistent fashion. By now, it is being explored how an experiment design can be useful to create a computational agent to be included within the platform. These inclusions of designed agents –or software pieces– are useful for the better accomplishment of the tasks to be developed by the platform. Clearly, while the number of agents increases the new version of the virtual laboratory thus enhances in robustness and functionality.

Keywords: genetic algorithms, multi-agent systems, bioinformatics, optimization, protein folding, structural biology.

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861 Stimulus-Dependent Polyrhythms of Central Pattern Generator Hardware

Authors: Le Zhao, Alain Nogaret

Abstract:

We have built universal central pattern generator (CPG) hardware by interconnecting Hodgkin-Huxley neurons with reciprocally inhibitory synapses. We investigate the dynamics of neuron oscillations as a function of the time delay between current steps applied to individual neurons. We demonstrate stimulus dependent switching between spiking polyrhythms and map the phase portraits of the neuron oscillations to reveal the basins of attraction of the system. We experimentally study the dependence of the attraction basins on the network parameters: The neuron response time and the strength of inhibitory connections.

Keywords: Central pattern generator, winnerless competition principle.

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860 Evaluating Content Based Image Retrieval Techniques with the One Million Images CLIC Test Bed

Authors: Pierre-Alain Moëllic, Patrick Hède, Gr egory Grefenstette, Christophe Millet

Abstract:

Pattern recognition and image recognition methods are commonly developed and tested using testbeds, which contain known responses to a query set. Until now, testbeds available for image analysis and content-based image retrieval (CBIR) have been scarce and small-scale. Here we present the one million images CEA-List Image Collection (CLIC) testbed that we have produced, and report on our use of this testbed to evaluate image analysis merging techniques. This testbed will soon be made publicly available through the EU MUSCLE Network of Excellence.

Keywords: CBIR, CLIC, evaluation, image indexing and retrieval, testbed.

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859 Modeling UWSN Simulators – A Taxonomy

Authors: Christhu Raj, Rajeev Sukumaran

Abstract:

In this research article of modeling Underwater Wireless Sensor Network Simulators, we provide a comprehensive overview of the various currently available simulators used in UWSN modeling. In this work, we compare their working environment, software platform, simulation language, key features, limitations and corresponding applications. Based on extensive experimentation and performance analysis, we provide their efficiency for specific applications. We have also provided guidelines for developing protocols in different layers of the protocol stack, and finally these parameters are also compared and tabulated. This analysis is significant for researchers and designers to find the right simulator for their research activities.

Keywords: Underwater Wireless Sensor networks (UWSN), SUNSET, NS2, OPNET, WOSS, DESERT, RECORDS, Aqua- Sim, Aqua- Net Mate.

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858 Tabu Search Approach to Solve Routing Issues in Communication Networks

Authors: Anant Oonsivilai, Wichai Srisuruk, Boonruang Marungsri, Thanatchai Kulworawanichpong

Abstract:

Optimal routing in communication networks is a major issue to be solved. In this paper, the application of Tabu Search (TS) in the optimum routing problem where the aim is to minimize the computational time and improvement of quality of the solution in the communication have been addressed. The goal is to minimize the average delays in the communication. The effectiveness of Tabu Search method is shown by the results of simulation to solve the shortest path problem. Through this approach computational cost can be reduced.

Keywords: Communication networks, optimum routing network, tabu search algorithm, shortest path.

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857 Multi-Agent Approach for Monitoring and Control of Biotechnological Processes

Authors: Ivanka Valova

Abstract:

This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: Multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation.

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856 An Architecture Based on Capsule Networks for the Identification of Handwritten Signature Forgery

Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

Abstract:

Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: Biometrics, deep learning, handwriting, signature forgery.

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855 Modeling of Statistically Multiplexed Non Uniform Activity VBR Video

Authors: J. P. Dubois

Abstract:

This paper reports the feasibility of the ARMA model to describe a bursty video source transmitting over a AAL5 ATM link (VBR traffic). The traffic represents the activity of the action movie "Lethal Weapon 3" transmitted over the ATM network using the Fore System AVA-200 ATM video codec with a peak rate of 100 Mbps and a frame rate of 25. The model parameters were estimated for a single video source and independently multiplexed video sources. It was found that the model ARMA (2, 4) is well-suited for the real data in terms of average rate traffic profile, probability density function, autocorrelation function, burstiness measure, and the pole-zero distribution of the filter model.

Keywords: ARMA, ATM networks, burstiness, multimediatraffic, VBR video.

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854 Modeling and Simulation of Dynamic Voltage Restorer for Mitigation of Voltage Sags

Authors: S. Ganesh, L. Raguraman, E. Anushya, J. krishnasree

Abstract:

Voltage sags are the most common power quality disturbance in the distribution system. It occurs due to the fault in the electrical network or by the starting of a large induction motor and this can be solved by using the custom power devices such as Dynamic Voltage Restorer (DVR). In this paper DVR is proposed to compensate voltage sags on critical loads dynamically. The DVR consists of VSC, injection transformers, passive filters and energy storage (lead acid battery). By injecting an appropriate voltage, the DVR restores a voltage waveform and ensures constant load voltage. The simulation and experimental results of a DVR using MATLAB software shows clearly the performance of the DVR in mitigating voltage sags.

Keywords: Dynamic voltage restorer, Voltage sags, Power quality, Injection methods.

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853 Prioritization Assessment of Housing Development Risk Factors: A Fuzzy Hierarchical Process-Based Approach

Authors: Yusuf Garba Baba

Abstract:

The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: Risk identification, risk assessment, analytical hierarchical process, multi-criteria decision.

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852 Convective Hot Air Drying of Different Varieties of Blanched Sweet Potato Slices

Authors: M. O. Oke, T. S. Workneh

Abstract:

Drying behavior of blanched sweet potato in a cabinet dryer using different five air temperatures (40-80°C) and ten sweet potato varieties sliced to 5mm thickness were investigated. The drying data were fitted to eight models. The Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data obtained during the drying of all the varieties while Newton (Lewis) and Wang and Singh models gave the least fit. The values of Deff obtained for Bophelo variety (1.27 x 10-9 to 1.77 x 10-9 m2/s) was the least while that of S191 (1.93 x 10-9 to 2.47 x 10-9 m2/s) was the highest which indicates that moisture diffusivity in sweet potato is affected by the genetic factor. Activation energy values ranged from 0.27-6.54 kJ/mol. The lower activation energy indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method. The drying behavior of blanched sweet potato was investigated in a cabinet dryer. Drying time decreased considerably with increase in hot air temperature. Out of the eight models fitted, the Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data on all the varieties while Newton, Wang and Singh models gave the least. The lower activation energy (0.27 - 6.54 kJ/mol) obtained indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method.

Keywords: Sweet Potato Slice, Drying Models, Moisture Ratio, Moisture Diffusivity, Activation Energy.

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851 Computer Countenanced Diagnosis of Skin Nodule Detection and Histogram Augmentation: Extracting System for Skin Cancer

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

Abstract:

Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: Computer-aided system, detection, image segmentation, morphology.

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850 Design of Smith-like Predictive Controller with Communication Delay Adaptation

Authors: Jasmin Velagic

Abstract:

This paper addresses the design of predictive networked controller with adaptation of a communication delay. The networked control system contains random delays from sensor to controller and from controller to actuator. The proposed predictive controller includes an adaptation loop which decreases the influence of communication delay on the control performance. Also, the predictive controller contains a filter which improves the robustness of the control system. The performance of the proposed adaptive predictive controller is demonstrated by simulation results in comparison with PI controller and predictive controller with constant delay.

Keywords: Predictive control, adaptation, communication delay, communication network.

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849 Big Data: Concepts, Technologies and Applications in the Public Sector

Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

Abstract:

Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: Big data, big data Analytics, Hadoop framework, cloud computing.

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848 Technique for Voltage Control in Distribution System

Authors: S. Thongkeaw, M. Boonthienthong

Abstract:

This paper presents the techniques for voltage control in distribution system. It is integrated in the distribution management system. Voltage is an important parameter for the control of electrical power systems. The distribution network operators have the responsibility to regulate the voltage supplied to consumer within statutory limits. Traditionally, the On-Load Tap Changer (OLTC) transformer equipped with automatic voltage control (AVC) relays is the most popular and effective voltage control device. A static synchronous compensator (STATCOM) may be equipped with several controllers to perform multiple control functions. Static Var Compensation (SVC) is regulation slopes and available margins for var dispatch. The voltage control in distribution networks is established as a centralized analytical function in this paper. 

Keywords: Voltage Control, Reactive Power, Distribution System.

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847 Capacity Optimization in Cooperative Cognitive Radio Networks

Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

Abstract:

Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: Cooperative networks, normalized capacity, sensing time.

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