Search results for: Park's vector approach

Authors: Shahram Mohammadi, Ali Frajzadeh

Abstract:

A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.

Keywords: Matching, Minutiae, Reference point, Reference orientation

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Authors: S. Raja Balachandar, K.Kannan

Abstract:

This paper presents a heuristic approach to solve the Generalized Assignment Problem (GAP) which is NP-hard. It is worth mentioning that many researches used to develop algorithms for identifying the redundant constraints and variables in linear programming model. Some of the algorithms are presented using intercept matrix of the constraints to identify redundant constraints and variables prior to the start of the solution process. Here a new heuristic approach based on the dominance property of the intercept matrix to find optimal or near optimal solution of the GAP is proposed. In this heuristic, redundant variables of the GAP are identified by applying the dominance property of the intercept matrix repeatedly. This heuristic approach is tested for 90 benchmark problems of sizes upto 4000, taken from OR-library and the results are compared with optimum solutions. Computational complexity is proved to be O(mn2) of solving GAP using this approach. The performance of our heuristic is compared with the best state-ofthe- art heuristic algorithms with respect to both the quality of the solutions. The encouraging results especially for relatively large size test problems indicate that this heuristic approach can successfully be used for finding good solutions for highly constrained NP-hard problems.

Keywords: Combinatorial Optimization Problem, Generalized Assignment Problem, Intercept Matrix, Heuristic, Computational Complexity, NP-Hard Problems.

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

Abstract:

We have conducted the optimal synthesis of rootmean- squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous - time.

Keywords: Mathematical expectation, filtration, anomalous noise, memory.

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Authors: Sahil, Rajeev Saha, Sanjeev Kumar

Abstract:

Material selection is one of the key issues for the production of reliable and quality products in industries. A number of materials are available for a single product due to which material selection become a difficult task. The aim of this paper is to select appropriate material for gear used in fuel pump by using Graph Theory and Matrix Approach (GTMA). GTMA is a logical and systematic approach that can be used to model and analyze various engineering systems. In present work, four alternative material and their seven attributes are used to identify the best material for given product.

Keywords: Material, GTMA, MADM, digraph, decision making.

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Authors: Ju H. Park, S.M. Lee

Abstract:

In this paper, we propose a robust controller design method for discrete-time systems with sector-bounded nonlinearities and time-varying delay. Based on the Lyapunov theory, delaydependent stabilization criteria are obtained in terms of linear matrix inequalities (LMIs) by constructing the new Lyapunov-Krasovskii functional and using some inequalities. A robust state feedback controller is designed by LMI framework and a reciprocally convex combination technique. The effectiveness of the proposed method is verified throughout a numerical example.

Keywords: Lur'e systems, Time-delay, Stabilization, LMIs.

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Authors: M. Bouri, L. Chraïbi, N. Sefiani

Abstract:

Currently, industries endeavor to align their environmental management system with the ISO 14001:2015 international standard, while preserving competitiveness and sustainability. Then, a key driver for these industries is to develop a skilled workforce that is able to implement, continuously improve and audit the environmental management system. The purpose of this paper is to provide an environmental competency framework that aims to identify, rank and categorize the competencies required by both the environmental managers and auditors. This competency framework is expected to be useful during competency assessment, recruitment, and training processes. To achieve this end, a modified 2-tuple Delphi approach is here proposed based on a combination of the modified Delphi approach and the 2-tuple linguistic representation model. The adopted approach is presented as numerous questionnaires that are spread over multiple rounds in order to obtain a consensus among the different Moroccan experts participating to this study.

Keywords: Competency framework, Delphi, environmental competency, 2-tuple.

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Authors: Sunho Ki, Daehwan Kim, Seongwon Cho, Sun-Tae Chung, Jaemin Kim, Yun-Kwang Hong, Chang Joon Park, Dongmin Kwon, Minhee Kang, Yusung Kim, Younghan Yoon

Abstract:

AAM (active appearance model) has been successfully applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard AAM-based face alignment method.

Keywords: AAM, Face Alignment, Feature Extraction, PCA

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Authors: Seongchan Kang, Hongsik Yun, Hyukgil Kim, Minwoo Park

Abstract:

For this study, this researcher conducted a precision network adjustment with QOCA, the precision network adjustment software developed by Jet Propulsion Laboratory, to perform an integrated network adjustment on the Unified Control Points managed by the National Geographic Information Institute. Towards this end, 275 Unified Control Points observed in 2008 were selected before a network adjustment is performed on those 275 Unified Control Points. The RMSE on the discrepancies of coordinates as compared to the results of GLOBK was ±6.07mm along the N axis, ±2.68mm along the E axis and ±6.49mm along the U axis.

Keywords: Network adjustment, QOCA, unified control point.

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Authors: Samy Sadek, Ayoub Al-Hamadi, Axel Panning, Bernd Michaelis, Usama Sayed

Abstract:

In this paper, we propose a novel approach for image segmentation via fuzzification of Rènyi Entropy of Generalized Distributions (REGD). The fuzzy REGD is used to precisely measure the structural information of image and to locate the optimal threshold desired by segmentation. The proposed approach draws upon the postulation that the optimal threshold concurs with maximum information content of the distribution. The contributions in the paper are as follow: Initially, the fuzzy REGD as a measure of the spatial structure of image is introduced. Then, we propose an efficient entropic segmentation approach using fuzzy REGD. However the proposed approach belongs to entropic segmentation approaches (i.e. these approaches are commonly applied to grayscale images), it is adapted to be viable for segmenting color images. Lastly, diverse experiments on real images that show the superior performance of the proposed method are carried out.

Keywords: Entropy of generalized distributions, entropy fuzzification, entropic image segmentation.

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Authors: Rekik Rima, Aouachria Mekki

Abstract:

We study the movement of a two-level atom in interaction with time dependent nonuniform magnetic filed using the path integral formalism. The propagator is first written in the standard form by replacing the spin by a unit vector aligned along the polar and azimuthal directions. Then it is determined exactly using perturbation methods. Thus the Rabi formula of the system are deduced.

Keywords: Path integral, Formalism, Propagator, Transition probability.

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Authors: Khalid Minaoui, Thierry Chonavel, Benayad Nsiri, Driss Aboutajdine

Abstract:

This paper deals with efficient quadrature formulas involving functions that are observed only at fixed sampling points. The approach that we develop is derived from efficient continuous quadrature formulas, such as Gauss-Legendre or Clenshaw-Curtis quadrature. We select nodes at sampling positions that are as close as possible to those of the associated classical quadrature and we update quadrature weights accordingly. We supply the theoretical quadrature error formula for this new approach. We show on examples the potential gain of this approach.

Keywords: Gauss-Legendre, Clenshaw-Curtis, quadrature, Peano kernel, irregular sampling.

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Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: Flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina.

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Authors: Ramin Halavati, Mansour Jamzad, Mahdieh Soleymani

Abstract:

Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in cases that the words where chosen from a prespecified list.

Keywords: Image Processing, Pattern Recognition.

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Authors: Yong Seo Koo, Dong Su Kim, Byung Seok Lee, Won Suk Park, Bo Bea Song

Abstract:

This paper presents a SCR-based ESD protection devices for I/O clamp and power rail clamp, respectably. These devices have a low trigger voltage and high holding voltage characteristics than conventional SCR device. These devices are fabricated by using 0.35um BCD (Bipolar-CMOS-DMOS) processes. These devices were validated using a TLP system. From the experimental results, the device for I/O ESD clamp has a trigger voltage of 5.8V. Also, the device for power rail ESD clamp has a holding voltage of 7.7V.

Keywords: ESD (Electro-Static Discharge), ESD protection device, SCR (Silicon Controlled Rectifier), Latch-up

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Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

Abstract:

With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: Location-based recommendation, map-reduce, recommendation system, trajectory search.

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Authors: N. Z. A. Hamid, M. S. M. Noorani

Abstract:

This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly Ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: Chaotic approach, phase space, Cao method, local linear approximation method.

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Authors: Kyrre M Begnum, Matthew Disney

Abstract:

Virtualization and high performance computing have been discussed from a performance perspective in recent publications. We present and discuss a flexible and efficient approach to the management of virtual clusters. A virtual machine management tool is extended to function as a fabric for cluster deployment and management. We show how features such as saving the state of a running cluster can be used to avoid disruption. We also compare our approach to the traditional methods of cluster deployment and present benchmarks which illustrate the efficiency of our approach.

Keywords: Cluster management, clusters, high-performance, virtual machines, Xen

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Authors: Liudmyla Koliechkina, Olena Dvirna

Abstract:

The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps.

Keywords: Discrete set, linear combinatorial optimization, multi-objective optimization, multipermutation, Pareto solutions, partial permutation set, permutation, structural graph.

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Authors: Chun-Lang Chang

Abstract:

According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.

Keywords: Data mining, Hearing impairment, Logistic regression analysis, Support vector machines

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Authors: Costin Pribeanu

Abstract:

The model-based approach to user interface design relies on developing separate models capturing various aspects about users, tasks, application domain, presentation and dialog structures. This paper presents a task modeling approach for user interface design and aims at exploring mappings between task, domain and presentation models. The basic idea of our approach is to identify typical configurations in task and domain models and to investigate how they relate each other. A special emphasis is put on applicationspecific functions and mappings between domain objects and operational task structures. In this respect, we will address two layers in task decomposition: a functional (planning) layer and an operational layer.

Keywords: task modeling, user interface design, unit tasks, basic tasks, operational task model.

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Authors: Yinggan Tang, Xinping Guan

Abstract:

Color image segmentation can be considered as a cluster procedure in feature space. k-means and its adaptive version, i.e. competitive learning approach are powerful tools for data clustering. But k-means and competitive learning suffer from several drawbacks such as dead-unit problem and need to pre-specify number of cluster. In this paper, we will explore to use competitive and cooperative learning approach to perform color image segmentation. In competitive and cooperative learning approach, seed points not only compete each other, but also the winner will dynamically select several nearest competitors to form a cooperative team to adapt to the input together, finally it can automatically select the correct number of cluster and avoid the dead-units problem. Experimental results show that CCL can obtain better segmentation result.

Keywords: Color image segmentation, competitive learning, cluster, k-means algorithm, competitive and cooperative learning.

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Authors: Steve Fish, Chris Lambert

Abstract:

Cumbria is a geo-political county in Northwest England within which the Lake District National Park, a UNESCO World Heritage site is located. Whilst the area has a formidable reputation for natural beauty and historic assets, the innovation ecosystem is described as ‘patchy’ for a number of reasons. The county is one of the largest in England by area and is sparsely populated. This paper describes the needs, development and delivery of an SME business-support programme funded by the European Regional Development Fund, Lancaster University and the University of Cumbria. The Cumbria Innovations Platform (CUSP) Project has been designed to respond to the nuanced needs of SMEs in this locale, whilst promoting the adoption of research and innovation. CUSP utilizes a funnel method to support rural businesses with access to university innovation intervention. CUSP has been built on a three-tier model: Communicate, Collaborate and Create. The paper describes this project in detail and presents results in terms of output indicators achieved, a beneficiary telephone survey and wider economic forecasts. From a pragmatic point-of-view, the paper provides experiences and reflections of those people who are delivering and evaluating knowledge exchange. The authors discuss some of the benefits, challenges and implications for both policy makers and practitioners. Finally, the paper aims to serve as an invitation to others who may consider adopting a similar method of university-industry collaboration in their own region.

Keywords: Regional business support, rural business support, university-industry collaboration, collaborative R&D, SMEs, knowledge exchange.

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Authors: A. Ourici

Abstract:

Doubly fed induction machines DFIM are used mainly for wind energy conversion in MW power plants. This paper presents a new strategy of field oriented control ,it is based on the principle of a double flux orientation of stator and rotor at the same time. Therefore, the orthogonality created between the two oriented fluxes, which must be strictly observed, leads to generate a linear and decoupled control with an optimal torque. The obtained simulation results show the feasibility and the effectiveness of the suggested method.

Keywords: Doubly fed induction machine, double fluxorientation control , vector control , PWM inverter.

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Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The paper proposes an approach for design of modular systems based on original technique for modeling and formulation of combinatorial optimization problems. The proposed approach is described on the example of personal computer configuration design. It takes into account the existing compatibility restrictions between the modules and can be extended and modified to reflect different functional and users- requirements. The developed design modeling technique is used to formulate single objective nonlinear mixedinteger optimization tasks. The practical applicability of the developed approach is numerically tested on the basis of real modules data. Solutions of the formulated optimization tasks define the optimal configuration of the system that satisfies all compatibility restrictions and user requirements.

Keywords: Constrained discrete combinatorial choice, modular systems design, optimization problem, PC configuration.

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Authors: Ling-fei Xu, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Shi-xue Xu

Abstract:

SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.

Keywords: SVM, predict, BOF, single spectrum intensity.

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Authors: Fei Hao, Hai Wang

Abstract:

One of research issues in social network analysis is to evaluate the position/importance of users in social networks. As the information diffusion in social network is evolving, it seems difficult to evaluate the importance of users using traditional approaches. In this paper, we propose an evaluation approach for user importance with fractal view in social networks. In this approach, the global importance (Fractal Importance) and the local importance (Topological Importance) of nodes are considered. The basic idea is that the bigger the product of fractal importance and topological importance of a node is, the more important of the node is. We devise the algorithm called TFRank corresponding to the proposed approach. Finally, we evaluate TFRank by experiments. Experimental results demonstrate our TFRank has the high correlations with PageRank algorithm and potential ranking algorithm, and it shows the effectiveness and advantages of our approach.

Keywords: TFRank, Fractal Importance, Topological Importance, Social Network

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Khalid M. Aamir, Mohammad A. Maud

Abstract:

Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).

Keywords: Power Spectral Density (PSD), Wiener-KhintchineTheorem, Periodogram, Short Time Fourier Transform (STFT), TheSliding DFT.

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Authors: Sanghoon Park, Kijin Kim, Kwangho Ahn

Abstract:

An active RC filters with a 880 / 1760 MHz dual bandwidth tuning ability is present for 60 GHz unlicensed band applications. A third order Butterworth low-pass filter utilizes two Cherry-Hooper amplifiers to satisfy the very high bandwidth requirements of an amplifier. The low-pass filter is fabricated in 90nm standard CMOS process. Drawing 6.7 mW from 1.2 V power supply, the low frequency gains of the filter are -2.5 and -4.1 dB, and the output third order intercept points (OIP3) are +2.2 and +1.9 dBm for the single channel and channel bonding conditions, respectively.

Keywords: Butterworth filter, active RC, 60 GHz, CMOS, dual bandwidth, Cherry-Hooper amplifier.

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Authors: M. Hussain, Aqsa Farooq

Abstract:

Let G = (V,E) be a connected graph and distance between any two vertices a and b in G is a−b geodesic and is denoted by d(a, b). A set of vertices W resolves a graph G if each vertex is uniquely determined by its vector of distances to the vertices in W. A metric dimension of G is the minimum cardinality of a resolving set of G. In this paper line graph of honeycomb network has been derived and then we calculated the metric dimension on line graph of honeycomb network.

Keywords: Resolving set, metric dimension, honeycomb network, line graph.

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