Search results for: Adaptive Network based Fuzzy Inference System (ANFIS)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17468

Search results for: Adaptive Network based Fuzzy Inference System (ANFIS)

8858 Standard Languages for Creating a Database to Display Financial Statements on a Web Application

Authors: Vladimir Simovic, Matija Varga, Predrag Oreski

Abstract:

XHTML and XBRL are the standard languages for creating a database for the purpose of displaying financial statements on web applications. Today, XBRL is one of the most popular languages for business reporting. A large number of countries in the world recognize the role of XBRL language for financial reporting and the benefits that the reporting format provides in the collection, analysis, preparation, publication and the exchange of data (information) which is the positive side of this language. Here we present all advantages and opportunities that a company may have by using the XBRL format for business reporting. Also, this paper presents XBRL and other languages that are used for creating the database, such XML, XHTML, etc. The role of the AJAX complex model and technology will be explained in detail, and during the exchange of financial data between the web client and web server. Here will be mentioned basic layers of the network for data exchange via the web.

Keywords: XHTML, XBRL, XML, JavaScript, AJAX technology, data exchange.

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8857 1/f Noise in Quantum-Size Heteronanostructures Based On GaAs and Alloys

Authors: Alexey V. Klyuev, Arkady. V. Yakimov

Abstract:

The 1/f noise investigation in nanoscale light-emitting diodes and lasers, based on GaAs and alloys, is presented here. Leakage and additional (to recombination through quantum wells and/or dots) nonlinear currents were detected and it was shown that these currents are the main source of the 1/f noise in devices studied.

Keywords: Lasers, light-emitting diodes, quantum dots, quantum wells, 1/f noise.

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8856 Analysis of Genotype Size for an Evolvable Hardware System

Authors: Emanuele Stomeo, Tatiana Kalganova, Cyrille Lambert

Abstract:

The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.

Keywords: Evolvable hardware, genotype size, computational intelligence, design of logic circuits.

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8855 Effects of Superheating on Thermodynamic Performance of Organic Rankine Cycles

Authors: Kyoung Hoon Kim

Abstract:

Recently ORC(Organic Rankine Cycle) has attracted much attention due to its potential in reducing consumption of fossil fuels and its favorable characteristics to exploit low-grade heat sources. In this work thermodynamic performance of ORC with superheating of vapor is comparatively assessed for various working fluids. Special attention is paid to the effects of system parameters such as the evaporating temperature and the turbine inlet temperature on the characteristics of the system such as maximum possible work extraction from the given source, volumetric flow rate per 1 kW of net work and quality of the working fluid at turbine exit as well as thermal and exergy efficiencies. Results show that for a given source the thermal efficiency increases with decrease of the superheating but exergy efficiency may have a maximum value with respect to the superheating of the working fluid. Results also show that in selection of working fluid it is required to consider various criteria of performance characteristics as well as thermal efficiency.

Keywords: organic Rankine cycle (ORC), low-grade energysource, Patel-Teja equation, thermodynamic performance

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8854 Personalization and the Universal Communications Identifier Concept

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

Abstract:

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

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

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8853 Towards End-To-End Disease Prediction from Raw Metagenomic Data

Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: Metagenomics, phenotype prediction, deep learning, embeddings, multiple instance learning.

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8852 Clustering Mixed Data Using Non-normal Regression Tree for Process Monitoring

Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek

Abstract:

In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.

Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.

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8851 A Security Cloud Storage Scheme Based Accountable Key-Policy Attribute-Based Encryption without Key Escrow

Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

Abstract:

With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: Cloud storage security, sharing storage, attributes, Hash algorithm.

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8850 Distillation Monitoring and Control using LabVIEW and SIMULINK Tools

Authors: J. Fernandez de Canete, P. Del Saz Orozco, S. Gonzalez-Perez

Abstract:

LabVIEW and SIMULINK are two most widely used graphical programming environments for designing digital signal processing and control systems. Unlike conventional text-based programming languages such as C, Cµ and MATLAB, graphical programming involves block-based code developments, allowing a more efficient mechanism to build and analyze control systems. In this paper a LabVIEW environment has been employed as a graphical user interface for monitoring the operation of a controlled distillation column, by visualizing both the closed loop performance and the user selected control conditions, while the column dynamics has been modeled under the SIMULINK environment. This tool has been applied to the PID based decoupled control of a binary distillation column. By means of such integrated environments the control designer is able to monitor and control the plant behavior and optimize the response when both, the quality improvement of distillation products and the operation efficiency tasks, are considered.

Keywords: Distillation control, software tools, SIMULINKLabVIEWinterface.

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8849 The Emission Spectra Due to Exciton-Exciton Collisions in GaAs/AlGaAs Quantum Well System

Authors: Surendra K Pandey

Abstract:

Optical emission based on excitonic scattering processes becomes important in dense exciton systems in which the average distance between excitons is of the order of a few Bohr radii but still below the exciton screening threshold. The phenomena due to interactions among excited states play significant role in the emission near band edge of the material. The theory of two-exciton collisions for GaAs/AlGaAs quantum well systems is a mild attempt to understand the physics associated with the optical spectra due to excitonic scattering processes in these novel systems. The four typical processes considered give different spectral shape, peak position and temperature dependence of the emission spectra. We have used the theory of scattering together with the second order perturbation theory to derive the radiative power spontaneously emitted at an energy ħω by these processes. The results arrived at are purely qualitative in nature. The intensity of emitted light in quantum well systems varies inversely to the square of temperature, whereas in case of bulk materials it simply decreases with the  temperature.

Keywords: Exciton-Exciton Collisions, Excitonic Scattering Processes, Interacting Excitonic States, Quantum Wells.

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8848 IIR Filter design with Craziness based Particle Swarm Optimization Technique

Authors: Suman Kumar Saha, Rajib Kar, Durbadal Mandal, S. P. Ghoshal

Abstract:

This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.

Keywords: IIR Filter, RGA, PSO, CRPSO, Evolutionary Optimization Techniques, Low Pass (LP) Filter, Magnitude Response, Pole-Zero Plot, Stability.

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8847 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Abstract:

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.

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8846 Panel Zone Rigidity Effects on Special Steel Moment-Resisting Frames According to the Performance Based Design

Authors: Mahmoud Miri, Morteza Naghipour, Amir Kashiryfar

Abstract:

The unanticipated destruct of more of the steel moment frames in Northridge earthquake, altered class of regard to the beamto- column connections in moment frames. Panel zone is one the significant part of joints which, it-s stiffness and rigidity has an important effect on the behavior and ductility of the frame. Specifically that behavior of panel zone has a very significant effect on the special moment frames. In this paper , meanwhile the relations for modeling of panel zone in frames are expressed , special moment frames with different spans and stories were studied in the way of performance-based design. The frames designed in according with Iranian steel building code. The effect of panel zone is also considered and in the case of non-existence of performance level, by changing in intimacies and parameter of panel zone, performance level is considered.

Keywords: steel moment frame, panel zone, performance based design

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8845 Cascaded Transcritical/Supercritical CO2 Cycles and Organic Rankine Cycles to Recover Low-Temperature Waste Heat and LNG Cold Energy Simultaneously

Authors: Haoshui Yu, Donghoi Kim, Truls Gundersen

Abstract:

Low-temperature waste heat is abundant in the process industries, and large amounts of Liquefied Natural Gas (LNG) cold energy are discarded without being recovered properly in LNG terminals. Power generation is an effective way to utilize low-temperature waste heat and LNG cold energy simultaneously. Organic Rankine Cycles (ORCs) and CO2 power cycles are promising technologies to convert low-temperature waste heat and LNG cold energy into electricity. If waste heat and LNG cold energy are utilized simultaneously in one system, the performance may outperform separate systems utilizing low-temperature waste heat and LNG cold energy, respectively. Low-temperature waste heat acts as the heat source and LNG regasification acts as the heat sink in the combined system. Due to the large temperature difference between the heat source and the heat sink, cascaded power cycle configurations are proposed in this paper. Cascaded power cycles can improve the energy efficiency of the system considerably. The cycle operating at a higher temperature to recover waste heat is called top cycle and the cycle operating at a lower temperature to utilize LNG cold energy is called bottom cycle in this study. The top cycle condensation heat is used as the heat source in the bottom cycle. The top cycle can be an ORC, transcritical CO2 (tCO2) cycle or supercritical CO2 (sCO2) cycle, while the bottom cycle only can be an ORC due to the low-temperature range of the bottom cycle. However, the thermodynamic path of the tCO2 cycle and sCO2 cycle are different from that of an ORC. The tCO2 cycle and the sCO2 cycle perform better than an ORC for sensible waste heat recovery due to a better temperature match with the waste heat source. Different combinations of the tCO2 cycle, sCO2 cycle and ORC are compared to screen the best configurations of the cascaded power cycles. The influence of the working fluid and the operating conditions are also investigated in this study. Each configuration is modeled and optimized in Aspen HYSYS. The results show that cascaded tCO2/ORC performs better compared with cascaded ORC/ORC and cascaded sCO2/ORC for the case study.

Keywords: LNG cold energy, low-temperature waste heat, organic Rankine cycle, supercritical CO2 cycle, transcritical CO2 cycle.

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8844 Neural Networks for Short Term Wind Speed Prediction

Authors: K. Sreelakshmi, P. Ramakanthkumar

Abstract:

Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depends on the values of other meteorological variables, such as atmospheric pressure, moisture content, humidity, rainfall etc. The values of these parameters are obtained from a nearest weather station and are used to train various forms of neural networks. The trained model of neural networks is validated using a similar set of data. The model is then used to predict the wind speed, using the same meteorological information. This paper reports an Artificial Neural Network model for short term wind speed prediction, which uses back propagation algorithm.

Keywords: Short term wind speed prediction, Neural networks, Back propagation.

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8843 Determination of the Best Fit Probability Distribution for Annual Rainfall in Karkheh River at Iran

Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best-fit probability distribution of annual rainfall based on 50 years sample (1966-2015) in the Karkheh river basin at Iran using six probability distributions: Normal, 2-Parameter Log Normal, 3-Parameter Log Normal, Pearson Type 3, Log Pearson Type 3 and Gumbel distribution. The best fit probability distribution was selected using Stormwater Management and Design Aid (SMADA) software and based on the Residual Sum of Squares (R.S.S) between observed and estimated values Based on the R.S.S values of fit tests, the Log Pearson Type 3 and then Pearson Type 3 distributions were found to be the best-fit probability distribution at the Jelogir Majin and Pole Zal rainfall gauging station. The annual values of expected rainfall were calculated using the best fit probability distributions and can be used by hydrologists and design engineers in future research at studied region and other region in the world.

Keywords: Log Pearson Type 3, SMADA, rainfall, Karkheh River.

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8842 ANN Models for Microstrip Line Synthesis and Analysis

Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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8841 Stabilization of Clay Soil Using A-3 Soil

Authors: Mohammed Mustapha Alhaji, Salawu Sadiku

Abstract:

A clay soil classified as A-7-6 and CH soil according to AASHTO and unified soil classification system respectively, was stabilized using A-3 soil (AASHTO soil classification system). The clay soil was replaced with 0%, 10%, 20%, to 100% A-3 soil, compacted at both British Standard Light (BSL) and British Standard Heavy (BSH) compaction energy levels and using Unconfined Compressive Strength (UCS) as evaluation criteria. The Maximum Dry Density (MDD) of the treated soils at both the BSL and BSH compaction energy levels showed increase from 0% to 40% A-3 soil replacement after which the values reduced to 100% replacement. The trend of the Optimum Moisture Content (OMC) with varied A-3 soil replacement was similar to that of MDD but in a reversed order. The OMC reduced from 0% to 40% A-3 soil replacement after which the values increased to 100% replacement. This trend was attributed to the observed reduction in void ratio from 0% to 40% replacement after which the void ratio increased to 100% replacement. The maximum UCS for the soil at varied A-3 soil replacement increased from 272 and 770 kN/m2 for BSL and BSH compaction energy level at 0% replacement to 295 and 795 kN/m2 for BSL and BSH compaction energy level respectively at 10% replacement after which the values reduced to 22 and 60 kN/m2 for BSL and BSH compaction energy level respectively at 70% replacement. Beyond 70% replacement, the mixtures could not be moulded for UCS test.

Keywords: A-3 soil, clay soil, pozzolanic action, stabilization.

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8840 Fractional Delay FIR Filters Design with Enhanced Differential Evolution

Authors: Krzysztof Walczak

Abstract:

Fractional delay FIR filters design method based on the differential evolution algorithm is presented. Differential evolution is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach, an evolutionary algorithm is used to determine the coefficients of a fractional delay FIR filter based on the Farrow structure. Basic differential evolution is enhanced with a restricted mating technique, which improves the algorithm performance in terms of convergence speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares method.

Keywords: Fractional Delay Filters, Farrow Structure, Evolutionary Computation, Differential Evolution

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8839 Analyzing Current Transformer’s Transient and Steady State Behavior for Different Burden’s Using LabVIEW Data Acquisition Tool

Authors: D. Subedi, D. Sharma

Abstract:

Current transformers (CTs) are used to transform large primary currents to a small secondary current. Since most standard equipment’s are not designed to handle large primary currents the CTs have an important part in any electrical system for the purpose of Metering and Protection both of which are integral in Power system. Now a days due to advancement in solid state technology, the operation times of the protective relays have come to a few cycles from few seconds. Thus, in such a scenario it becomes important to study the transient response of the current transformers as it will play a vital role in the operating of the protective devices.

This paper shows the steady state and transient behavior of current transformers and how it changes with change in connected burden. The transient and steady state response will be captured using the data acquisition software LabVIEW. Analysis is done on the real time data gathered using LabVIEW. Variation of current transformer characteristics with changes in burden will be discussed.

Keywords: Accuracy, Accuracy limiting factor, Burden, Current Transformer, Instrument Security factor.

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8838 Slovenian Text-to-Speech Synthesis for Speech User Interfaces

Authors: Jerneja Žganec Gros, Aleš Mihelič, Nikola Pavešić, Mario Žganec, Stanislav Gruden

Abstract:

The paper presents the design concept of a unitselection text-to-speech synthesis system for the Slovenian language. Due to its modular and upgradable architecture, the system can be used in a variety of speech user interface applications, ranging from server carrier-grade voice portal applications, desktop user interfaces to specialized embedded devices. Since memory and processing power requirements are important factors for a possible implementation in embedded devices, lexica and speech corpora need to be reduced. We describe a simple and efficient implementation of a greedy subset selection algorithm that extracts a compact subset of high coverage text sentences. The experiment on a reference text corpus showed that the subset selection algorithm produced a compact sentence subset with a small redundancy. The adequacy of the spoken output was evaluated by several subjective tests as they are recommended by the International Telecommunication Union ITU.

Keywords: text-to-speech synthesis, prosody modeling, speech user interface.

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8837 Investigation of Maritime Accidents with Exploratory Data Analysis in the Strait of Çanakkale (Dardanelles)

Authors: Gizem Kodak

Abstract:

The Strait of Çanakkale (Dardanelles), together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: Maritime Accidents, EDA, Strait of Çanakkale, navigational safety.

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8836 A Study of Gaps in CBMIR Using Different Methods and Prospective

Authors: Pradeep Singh, Sukhwinder Singh, Gurjinder Kaur

Abstract:

In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.

Keywords: Classification, clustering, content-based image retrieval (CBIR), relevance feedback (RF), statistical similarity matching, support vector machine (SVM).

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8835 Study of Reporting System for Adverse Events Related to Common Medical Devices at a Tertiary Care Public Sector Hospital in India

Authors: S. Kurien, S. Satpathy, S. K. Gupta, S. K. Arya, D. K. Sharma

Abstract:

Advances in the use of health care technology have resulted in increased adverse events (AEs) related to the use of medical devices. The study focused on the existing reporting systems. This study was conducted in a tertiary care public sector hospital. Devices included Syringe infusion pumps, Cardiac monitors, Pulse oximeters, Ventilators and Defibrillators. A total of 211 respondents were recruited. Interviews were held with 30 key informants. Medical records were scrutinized. Relevant statistical tests were used. Resident doctors reported maximum frequency of AEs, followed by nurses; and least by consultants. A significant association was found between the cadre of health care personnel and awareness that the patients and bystanders have a risk of sustaining AE. Awareness regarding reporting of AEs was low, and it was generally done verbally. Other critical findings are discussed in the light of the barriers to reporting, reasons for non-compliance, recording system, and so on.

Keywords: Adverse events, health care technology, public sector hospital, reporting systems.

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8834 Independent Design of Multi-loop PI/PID Controllers for Multi-delay Processes

Authors: Truong Nguyen Luan Vu, Moonyong Lee

Abstract:

The interactions between input/output variables are a very common phenomenon encountered in the design of multi-loop controllers for interacting multivariable processes, which can be a serious obstacle for achieving a good overall performance of multiloop control system. To overcome this impediment, the decomposed dynamic interaction analysis is proposed by decomposing the multiloop control system into a set of n independent SISO systems with the corresponding effective open-loop transfer function (EOTF) within the dynamic interactions embedded explicitly. For each EOTF, the reduced model is independently formulated by using the proposed reduction design strategy, and then the paired multi-loop proportional-integral-derivative (PID) controller is derived quite simply and straightforwardly by using internal model control (IMC) theory. This design method can easily be implemented for various industrial processes because of its effectiveness. Several case studies are considered to demonstrate the superior of the proposed method.

Keywords: Multi-loop PID controller, internal model control(IMC), effective open-loop transfer function (EOTF)

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8833 Preliminary Chaos Analyses of Explosion Earthquakes Followed by Harmonic Tremors at Semeru Volcano, East Java, Indonesia

Authors: Sukir Maryanto, Didik R. Santosa, Iyan Mulyana, Muhammad Hendrasto

Abstract:

Successive event of explosion earthquake and harmonic tremor recorded at Semeru volcano were analyzed to investigate the dynamical system regarding to their eruptive mechanism. The eruptive activity at Semeru volcano East Java, Indonesia is intermittent emission of ash and bombs with Strombolian style which occurred at interval of 15 to 45 minutes. The explosive eruptions accompanied by explosion earthquakes and followed by volcanic tremor which generated by continuous emission of volcanic ash. The spectral and Lyapunov exponent of successive event of explosion and harmonic tremor were analyzed. Peak frequencies of explosion earthquakes range 1.2 to 1.9 Hz and those of the harmonic tremor have peak frequency range 1.5 — 2.2 Hz. The phase space is reconstructed and evaluated based on the Lyapunov exponents. Harmonic tremors have smaller Lyapunov exponent than explosion earthquakes. It can be considerably as correlated complexity of the mechanism from the variance of spectral and fractal dimension and can be concluded that the successive event of harmonic tremor and explosions are chaotic.

Keywords: Semeru volcano, explosion earthquakes, harmonic tremor, lyapunov exponent, chaotic.

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8832 Graph-Based Text Similarity Measurement by Exploiting Wikipedia as Background Knowledge

Authors: Lu Zhang, Chunping Li, Jun Liu, Hui Wang

Abstract:

Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.

Keywords: Text classification, Text clustering, Text similarity, Wikipedia

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8831 Comparative Spatial Analysis of a Re-arranged Hospital Building

Authors: Burak Köken, Hatice D. Arslan, Bilgehan Y. Çakmak

Abstract:

Analyzing the relation networks between the hospital buildings which have complex structure and distinctive spatial relationships is quite difficult. The hospital buildings which require specialty in spatial relationship solutions during design and selfinnovation through the developing technology should survive and keep giving service even after the disasters such as earthquakes. In this study, a hospital building where the load-bearing system was strengthened because of the insufficient earthquake performance and the construction of an additional building was required to meet the increasing need for space was discussed and a comparative spatial evaluation of the hospital building was made with regard to its status before the change and after the change. For this reason, spatial organizations of the building before change and after the change were analyzed by means of Space Syntax method and the effects of the change on space organization parameters were searched by applying an analytical procedure. Using Depthmap UCL software, Connectivity, Visual Mean Depth, Beta and Visual Integration analyses were conducted. Based on the data obtained after the analyses, it was seen that the relationships between spaces of the building increased after the change and the building has become more explicit and understandable for the occupants. Furthermore, it was determined according to findings of the analysis that the increase in depth causes difficulty in perceiving the spaces and the changes considering this problem generally ease spatial use.

Keywords: Architecture, hospital building, space syntax, strengthening.

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8830 Compiler-Based Architecture for Context Aware Frameworks

Authors: Hossein Nejati, Seyed H. Mirisaee, Gholam H. Dastghaibifard

Abstract:

Computers are being integrated in the various aspects of human every day life in different shapes and abilities. This fact has intensified a requirement for the software development technologies which is ability to be: 1) portable, 2) adaptable, and 3) simple to develop. This problem is also known as the Pervasive Computing Problem (PCP) which can be implemented in different ways, each has its own pros and cons and Context Oriented Programming (COP) is one of the methods to address the PCP. In this paper a design for a COP framework, a context aware framework, is presented which has eliminated weak points of a previous design based on interpreter languages, while introducing the compiler languages power in implementing these frameworks. The key point of this improvement is combining COP and Dependency Injection (DI) techniques. Both old and new frameworks are analyzed to show advantages and disadvantages. Finally a simulation of both designs is proposed to indicating that the practical results agree with the theoretical analysis while the new design runs almost 8 times faster.

Keywords: Dependency Injection, Compiler-based architecture, Context-Oriented Programming, COP, Pervasive ComputingProblem

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8829 A Study on the Average Information Ratio of Perfect Secret-Sharing Schemes for Access Structures Based On Bipartite Graphs

Authors: Hui-Chuan Lu

Abstract:

A perfect secret-sharing scheme is a method to distribute a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of participants in any unqualified subset is statistically independent of the secret. The collection of all qualified subsets is called the access structure of the perfect secret-sharing scheme. In a graph-based access structure, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme  realizing the access structure based on G is defined as AR = (Pv2V (G) H(v))/(|V (G)|H(s)), where s is the secret and v is the share of v, both are random variables from  and H is the Shannon entropy. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing a given access structure is called the optimal average information ratio of that access structure. Most known results about the optimal average information ratio give upper bounds or lower bounds on it. In this present structures based on bipartite graphs and determine the exact values of the optimal average information ratio of some infinite classes of them.

Keywords: secret-sharing scheme, average information ratio, star covering, core sequence.

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