Search results for: small signal modeling

Authors: Yoonsuh Jung

Abstract:

As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: A. Lovascio, A. D’Orazio, V. Centonze

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From several years till now the aerospace industry is developing more and more small satellites for Low-Earth Orbit (LEO) missions. Such satellites have a low cost of making and launching since they have a size and weight smaller than other types of satellites. However, because of size limitations, small satellites need integrated electronic equipment based on digital logic. Moreover, the LEOs require telecommunication modules with high throughput to transmit to earth a big amount of data in a short time. In order to meet such requirements, in this paper we propose a Telemetry, Tracking & Command module optimized through the use of the Commercial Off-The-Shelf components. The proposed approach exploits the major flexibility offered by these components in reducing costs and optimizing the performance. The method has been applied in detail for the design of the front-end receiver, which has a low noise figure (1.5 dB) and DC power consumption (smaller than 2 W). Such a performance is particularly attractive since it allows fulfilling the energy budget stringent constraints that are typical for LEO small platforms.

Keywords: COTS, LEO, small-satellite, TT&C

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Authors: Amirhosein Moonesi Shabestary, Eckhard Krepper, Dirk Lucas

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The current PhD project comprises CFD-modeling and simulation of condensation and heat transfer inside horizontal pipes. Condensation plays an important role in emergency cooling systems of reactors. The emergency cooling system consists of inclined horizontal pipes which are immersed in a tank of subcooled water. In the case of an accident the water level in the core is decreasing, steam comes in the emergency pipes, and due to the subcooled water around the pipe, this steam will start to condense. These horizontal pipes act as a strong heat sink which is responsible for a quick depressurization of the reactor core when any accident happens. This project is defined in order to model all these processes which happening in the emergency cooling systems. The most focus of the project is on detection of different morphologies such as annular flow, stratified flow, slug flow and plug flow. This project is an ongoing project which has been started 1 year ago in Helmholtz Zentrum Dresden Rossendorf (HZDR), Fluid Dynamics department. In HZDR most in cooperation with ANSYS different models are developed for modeling multiphase flows. Inhomogeneous MUSIG model considers the bubble size distribution and is used for modeling small-scaled dispersed gas phase. AIAD (Algebraic Interfacial Area Density Model) is developed for detection of the local morphology and corresponding switch between them. The recent model is GENTOP combines both concepts. GENTOP is able to simulate co-existing large-scaled (continuous) and small-scaled (polydispersed) structures. All these models are validated for adiabatic cases without any phase change. Therefore, the start point of the current PhD project is using the available models and trying to integrate phase transition and wall condensing models into them. In order to simplify the idea of condensation inside horizontal tubes, 3 steps have been defined. The first step is the investigation of condensation inside a horizontal tube by considering only direct contact condensation (DCC) and neglect wall condensation. Therefore, the inlet of the pipe is considered to be annular flow. In this step, AIAD model is used in order to detect the interface. The second step is the extension of the model to consider wall condensation as well which is closer to the reality. In this step, the inlet is pure steam, and due to the wall condensation, a liquid film occurs near the wall which leads to annular flow. The last step will be modeling of different morphologies which are occurring inside the tube during the condensation via using GENTOP model. By using GENTOP, the dispersed phase is able to be considered and simulated. Finally, the results of the simulations will be validated by experimental data which will be available also in HZDR.

Keywords: wall condensation, direct contact condensation, AIAD model, morphology detection

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Authors: Abigail Rosenberg, Jennifer Duan, Michael Poteuck, Chunshui Yu

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The Barry M. Goldwater Range, West in southwestern Arizona encompasses 2,808 square kilometers of Sonoran Desert. The hyper-arid range has an annual rainfall of less than 10 cm with an average high temperature of 41 degrees Celsius in July to an average low of 4 degrees Celsius in January. The range shares approximately 60 kilometers of the international border with Mexico. A majority of the range is open for recreational use, primarily off-highway vehicles. Because of its proximity to Mexico, the range is also heavily patrolled by U.S. Customs and Border Protection seeking to intercept and apprehend inadmissible people and illicit goods. Decades of off-roading and Border Patrol activities have negatively impacted this sensitive desert ecosystem. To assist the range program managers, this study is developing a model to identify erosion prone areas and calibrate the model’s parameters using the Automated Geospatial Watershed Assessment modeling tool.

Keywords: arid lands, automated geospatial watershed assessment, erosion modeling, sedimentation modeling, watershed modeling

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Authors: Igor A. Podgorny

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TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

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Authors: Y. Kobori, S. Tanaka, N. Tsukiji, N. Takai, H. Kobayashi

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This paper proposes two kinds of new single-inductor dual-output (SIDO) DC-DC switching converters with ripple-based hysteretic control. First SIDO converters of type 1 utilize the triangular signal generated by the CR-circuit connected across the inductor. This triangular signal is used for generating the PWM signal instead of the saw-tooth signal used in the conventional converters. Second SIDO converters of type 2 utilize the triangular signal generated by the CR-circuit connected across the voltage error amplifier. This paper describes circuit topologies, Operation principles, simulation results and experimental results of the proposed SIDO converters. In simulation results of both type of SIDO converters, static output voltage ripples are less than 5mVpp and over/under shoots of the dynamic load regulations for the output current step are less than +/- 10mV. In experimental results of single output converter of type 2, static output voltage ripples are about 20mVpp. Output ripples of SIDO type 1 converter are about 80mVpp.

Keywords: DC-DC converter, switching converter, SIDO converter, hysteretic control, ripple-based control

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Authors: Meriem Boukais, B. Dennai, A. Ould- Abbas

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The efficiency of SiGe solar cells might be improved by a wide-band-gap window layer. In this work we were simulated using the one dimensional simulation program called analysis of microelectronic and photonic structures (AMPS-1D). In the modeling, the thickness of silicon window was varied from 80 to 150 nm. The rest of layer’s thicknesses were kept constant, by varying thickness of window layer the simulated device performance was demonstrate in the form of current-voltage (I-V) characteristics and quantum efficiency (QE).

Keywords: modeling, SiGe, AMPS-1D, quantum efficiency, conversion, efficiency

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Authors: Akinwale Olusola Mokayode, Emaanuel Adu, Seriki Idowu Ibrahim

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Small business can serve as a tool for poverty reduction in South Africa, but it requires adequate support and development for its continuous sustenance in spite of rigorous challenges, especially in the rural environment. This study explored the challenges faced by the small business owners in the rural Eastern Cape Province of South Africa. The objective of the study is to identify the challenges faced by small business owners in the case study area and to examine the effects of those challenges on poverty rate. Survey research design was adopted, with the distribution of structured questionnaire for data collection through a simple random sampling method. Descriptive and inferential statistics was used to analyse the data. Findings showed that small business owners face various challenges in their commercial operations. It was also made clearer that these challenges have effects on the poverty rate as well as crime rate. In conclusion, in other for small businesses to be effective instrument to tackle poverty, certain measure must be taken into considerations. This therefore necessitates recommendation from the researcher that potential and current business owners must seek valuable advice from the more experienced business tycoon and seek information about the business assistance programmes provided by government and private sectors.

Keywords: eastern cape, poverty, poverty reduction, rural, small business, sustainable livelihood

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

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Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear modeling, NNARX

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Authors: Lemuel David

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The importance of the Micro, Small, and Medium Enterprises sector is well recognized for its legitimate contribution to the Macroeconomic objectives of the Republic of Liberia, like generation of employment, input t, exports, and enhancing entrepreneurship. Right now, Medium and Small enterprises accounts for about 99 percent of the industrial units in the country, contributing 60 percent of the manufacturing sector output and approximately one-third of the nation’s exports. The role of various financial institutions like ECO bank and Non-financial Institutions like Bearch Limited support promoting the growth of Micro, Small, and Medium Enterprises is unique. A small enterprise or entrepreneur gets many types of assistance from different institutions for varied purposes in the course of his entrepreneurial journey. This paper focuses on the factors related to financial institutional support and non-financial institutional support entrepreneurs to the growth of Medium and Small enterprises in the Republic of Liberia. The significance of this paper is to support Policy and Institutional Support for Medium and Small enterprises to know the views of entrepreneurs about financial and non-financial support systems in the Republic of Liberia. This study was carried out through a survey method, with the use of questionnaires. The population for this study consisted of all registered Medium and Small enterprises which have been registered during the years 2004-2014 in the republic of Liberia. The sampling method employed for this study was a simple random technique and determined a sample size of 400. Data for the study was collected using a standard questionnaire. The questionnaire consisted of two parts: the first part consisted of questions on the profile of the respondents. The second part covers (1) financial, promotional factors and (2) non-financial promotional factors. The results of the study are based on financial and non-financial supporting activities provided by institutions to Medium and Small enterprises. After investigation, it has been found that there is no difference in the support given by Financial Institutions and non-financial Institutions. Entrepreneurs perceived “collateral-free schemes and physical infrastructure support factors are highest contributing to entry and growth of Medium and Small enterprises.

Keywords: micro, small, and medium enterprises financial institutions, entrepreneurship

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Authors: Reza Ziaie Moayed, Ehsan Azini

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Jet grouting (JG) is one of the methods of improving and increasing the strength and bearing of soil in which the high pressure water or grout is injected through the nozzles into the soil. During this process, a part of the soil and grout particles comes out of the drill borehole, and the other part is mixed up with the grout in place, as a result of this process, a mass of modified soil is created. The purpose of this method is to change the soil into a mixture of soil and cement, commonly known as "soil-cement". In this paper, first, the principles of high pressure injection and then the effective parameters in the JG method are described. Then, the tests on the samples taken from the columns formed from the excavation around the soil-cement columns, as well as the static loading test on the created column, are discussed. In the other part of this paper, the soil behavior models for numerical modeling in PLAXIS software are mentioned. The purpose of this paper is to evaluate the results of numerical modeling based on in-situ static loading tests. The results indicate an acceptable agreement between the results of the tests mentioned and the modeling results. Also, modeling with this software as an appropriate option for technical feasibility can be used to soil improvement using JG.

Keywords: jet grouting column, soil improvement, numerical modeling, in-situ loading test

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Authors: Mustapha Shitu Suleiman, Francis Neshamba, Nestor Valero-Silva

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Small businesses are considered as engine of economic growth, contributing to employment generation, wealth creation, and poverty alleviation and food security in both developed and developing countries. Nigeria is facing many socio-economic problems and it is believed that by supporting small business development, as propellers of new ideas and more effective users of resources, often driven by individual creativity and innovation, Nigeria would be able to address some of its economic and social challenges, such as unemployment and economic diversification. Using secondary literature, this paper examines the role small businesses can play in the creation of jobs in North-West Nigeria to overcome issues of unemployment, which is the most devastating economic challenge facing the region. Most studies in this area have focused on Nigeria as a whole and only a few studies provide a regional focus, hence, this study will contribute to knowledge by filling this gap by concentrating on North-West Nigeria. It is hoped that with the present administration’s determination to improve the economy, small businesses would be used as vehicles for diversification of the economy away from crude oil to create jobs that would lead to a reduction in the country’s high unemployment level.

Keywords: job creation, north-west, Nigeria, small business, unemployment

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Authors: Jianguo Huang, Hong Cai, Bin Dong, Jifang Tao, Aiqun Liu, Dim-Lee Kwong, Yuandong Gu

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We developed a miniaturized tunable optomechanical oscillator based on the nanoelectromechanical systems (NEMS) technology, and its frequencies can be electrostatically tuned by as much as 10%. By taking both advantages of optical and electrical spring, the oscillator achieves a high tuning sensitivity without resorting to mechanical tension. In particular, the proposed high-Q optical cavity design greatly enhances the system sensitivity, making it extremely sensitive to the small motional signal.

Keywords: nanoelectromechanical systems (NEMS), nanotechnology, optical force, oscillator

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Authors: Kharaishvili Eteri

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The article highlights the importance of small and medium-sized enterprises in achieving the goals of sustainable development of the economy and increasing the well-being of the population. The opinion is put forward that it is necessary to adapt the activities of small and medium-sized firms in Georgia to sustainable business models. Therefore, it is important to identify the challenges that will ensure compliance with the goals and requirements of sustainable development of small and mediumsized enterprises. Objectives. The goal of the study is to reveal the challenges of sustainable development in small and medium-sized enterprises in Georgia and to develop recommendations for strategic development opportunities. Methodologies The challenges of sustainable development of small and medium-sized enterprises are investigated with the following methodology: bibliographic research of scientific works and reports of organizations is carried out; Based on the grouping of sustainable development goals, the performance indicators of these goals are studied; Differences with respect to the corresponding indicators of European countries are determined by the comparison method; The matrix scheme establishes the conditions and tools for sustainable development; Challenges of sustainable development are identified by factor analysis. Contributions Trends in the sustainable development of small and medium-sized enterprises are studied from the point of view of economic, social and environmental factors; To ensure sustainability, the conditions and tools for sustainable development are established (certified supply chains and global markets, allocation of financial resources necessary for sustainable development, proper public procurement, highly qualified workforce, etc.); Several main challenges have been identified in the sustainable development of small and medium-sized enterprises, including: limited internal resources; Institutional factors, especially vague and imperfect regulations, bureaucracy; low level of investments; Low level of qualification of human capital and others.

Keywords: small and medium-sized enterprises, sustainable development, conditions of sustainable development, strategic directions of sustainable development.

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Authors: Suparman

Abstract:

This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Haiyang Su, Kun Qian

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We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis.

Keywords: plasmonic materials, laser desorption/ionization, mass spectrometry, small nutrients, toxins

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Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Rony Reátegui, Cesar Chácara, Benjamin Castañeda, Rafael Aguilar

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Nowadays, heritage building information modeling (HBIM) is considered an efficient tool to represent and manage information of cultural heritage (CH). The basis of this tool relies on a 3D model generally obtained from a cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired level of development (LOD), level of information (LOI), grade of generation (GOG), as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit, and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings, and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills, and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models families, respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI, and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources since the BIM software used has a free student license.

Keywords: cloud-to-BIM, cultural heritage, generative modeling, HBIM, parametric modeling, Revit

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: H. Shokouhmand, M. Degheh, B. Sajadi, H. Sobhani

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The induct ultraviolet germicidal irradiation (UVGI) systems are broadly used nowadays and their utilization is widened every day. Even though these systems are not applicable individually, they are very suitable supplements for the traditional filtration systems. The amount of inactivated microorganisms is dependent on the air velocity, lamp power, fluence rate distribution, and also germicidal susceptibility of microorganisms. In this paper, these factors are investigated utilizing an air-microorganism two-phase numerical model. The eulerian-lagrangian method was used to have more detailed information on the history of each particle. The UVGI system was modeled in three steps including: 1) modeling the air flow, 2) modeling the discrete phase of particles, 3) modeling the UV intensity field, and 4) modeling the particle inactivation. The results from modeling different lamp arrangements and powers showed that the system functions better at more homogeneous irradiation distribution. Since increasing the air flow rate of the device results in increasing of particle inactivation rate, the optimal air velocity shall be adjusted in accordance with the microorganism production rate, and the air quality requirement using the curves represented in this paper.

Keywords: CFD, microorganism, two-phase flow, ultraviolet germicidal irradiation

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.

Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing

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Authors: Yanqun Li, Hong Geng

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The rapid urbanization process taking big cities as the main body leads to the unequal configuration of urban and rural areas in the aspects of land supply, industrial division of labor, service supply and space allocation, and induces the shrinking characterization of service energy, industrial system and population vitality in small towns. As an important spatial unit in the spectrum of urbanization that serves, connects and couples urban and rural areas, the shrinking phenomenon faced by small towns has an important influence on the healthy development of urbanization. Based on the census of small towns in Wuhan metropolitan area, we have found that the shrinking of small towns is a passive contraction of elastic tension under the squeeze in cities. Once affected by the external forces such as policy regulation, planning guidance, and population return, small towns will achieve expansion and growth. Based on the theory of complex adaptive systems, this paper comprehensively constructs the development index evaluation system of small towns from five aspects of population, economy, space, society and ecology, measures the shrinking level of small towns, further analyzes the shrinking characteristics of small towns, and identifies whether the shrinking is elastic or not. And then this paper measures the resilience ability index of small town contract from the above-mentioned five aspects. Finally, this paper proposes an adaptive mechanism of urban-rural interaction evolution under fine division of labor to response the passive shrinking in small towns of Wuhan. Based on the above, the paper creatively puts forward the planning response measures of the small towns on the aspects of spatial layout, function orientation and service support, which can provide reference for other regions.

Keywords: complex adaptive systems, resiliency shrinking, adaptation mechanism, planning response

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB/Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind energy, PWM inverter, modeling

Procedia PDF Downloads 287

Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: C. Yin, B. Zhang, Y. Liu, J. Cai

Abstract:

Airborne EM (AEM) is an effective geophysical exploration tool, especially suitable for ridged mountain areas. In these areas, topography will have serious effects on AEM system responses. However, until now little study has been reported on topographic effect on airborne EM systems. In this paper, an edge-based unstructured finite-element (FE) method is developed for 3D topographic modeling for both frequency and time-domain airborne EM systems. Starting from the frequency-domain Maxwell equations, a vector Helmholtz equation is derived to obtain a stable and accurate solution. Considering that the AEM transmitter and receiver are both located in the air, the scattered field method is used in our modeling. The Galerkin method is applied to discretize the Helmholtz equation for the final FE equations. Solving the FE equations, the frequency-domain AEM responses are obtained. To accelerate the calculation speed, the response of source in free-space is used as the primary field and the PARDISO direct solver is used to deal with the problem with multiple transmitting sources. After calculating the frequency-domain AEM responses, a Hankel’s transform is applied to obtain the time-domain AEM responses. To check the accuracy of present algorithm and to analyze the characteristic of topographic effect on airborne EM systems, both the frequency- and time-domain AEM responses for 3 model groups are simulated: 1) a flat half-space model that has a semi-analytical solution of EM response; 2) a valley or hill earth model; 3) a valley or hill earth with an abnormal body embedded. Numerical experiments show that close to the node points of the topography, AEM responses demonstrate sharp changes. Special attentions need to be paid to the topographic effects when interpreting AEM survey data over rugged topographic areas. Besides, the profile of the AEM responses presents a mirror relation with the topographic earth surface. In comparison to the topographic effect that mainly occurs at the high-frequency end and early time channels, the EM responses of underground conductors mainly occur at low frequencies and later time channels. For the signal of the same time channel, the dB/dt field reflects the change of conductivity better than the B-field. The research of this paper will serve airborne EM in the identification and correction of the topographic effects.

Keywords: 3D, Airborne EM, forward modeling, topographic effect

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Authors: Junyou Shi, Weiwei Cui

Abstract:

Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.

Keywords: fault detection, fault isolation, testability modeling, BIT

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Authors: Inseon Ryoo, Soo Chin Kim, Hyena Jung, Sangil Suh

Abstract:

Objectives: The purpose of this study is to evaluate the clinical significance of hyper-intense signal thyroid incidentalomas on the time of flight magnetic resonance angiography (TOF-MRA) using correlation study with ultrasound (US). Methods: We retrospectively reviewed 3,505 non-contrast TOF-MRA performed at an institution between September 2014 and May 2017. Two radiologists correlated the thyroid incidentalomas detected on TOF-MRA with US features which was obtained within three months interval between MRA and US examinations in consensus method. Results: The prevalence of hyper-intense signal thyroid nodules incidentally detected on TOF-MRA was 1.2% (43/3505). Among them, 35 people (81.4%) underwent US examinations, and total 45 hyper-intense signal thyroid nodules were detected on US exams. Of these 45 nodules, 35 nodules (72.9%) were categorized as benign (K-TIRADS category 2) on US exams. Fine needle aspiration was performed on 9 nodules according to the indications recommended by Korean Society of Thyroid Radiology. All except one high-suspicious thyroid nodule were confirmed as benign (Bethesda 2) on cytologic exams. One high-suspicious nodule on US showed a non-diagnostic result (Bethesda 1) on cytologic exam. However, this nodule collapsed after aspiration of thick colloid material. Conclusions: Our study showed that the most hyper-intense signal thyroid nodules detected on TOF-MRA were benign. Therefore, if a hyper-intense signal incidentaloma is found on TOF-MRA, further evaluation, especially invasive biopsy of the nodules could be suspended unless the patient had other symptoms or clinical factors suggesting the need for further evaluation.

Keywords: incidentaloma, thyroid nodule, TOF MR angiography, ultrasound

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