Search results for: Analysis methods

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.

Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.

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Authors: Salah Alrabeei, Mohammad Yousuf

Abstract:

The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.

Keywords: Integral differential equations, L-stable methods, pricing European options, Jump–diffusion model.

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Authors: Yueming Wang, Zenghui Zhang, Rendong Ying, Peilin Liu

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Sparse representation has long been studied and several dictionary learning methods have been proposed. The dictionary learning methods are widely used because they are adaptive. In this paper, a new dictionary learning method for audio is proposed. Signals are at first decomposed into different degrees of Intrinsic Mode Functions (IMF) using Empirical Mode Decomposition (EMD) technique. Then these IMFs form a learned dictionary. To reduce the size of the dictionary, the K-means method is applied to the dictionary to generate a K-EMD dictionary. Compared to K-SVD algorithm, the K-EMD dictionary decomposes audio signals into structured components, thus the sparsity of the representation is increased by 34.4% and the SNR of the recovered audio signals is increased by 20.9%.

Keywords: Dictionary Learning, EMD, K-means Method, Sparse Representation.

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Authors: Iveta Řepková

Abstract:

The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: Data Envelopment Analysis, efficiency, Slovak banking sector, window analysis.

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Authors: Salinee Thumronglaohapun

Abstract:

The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: Location-allocation problem, stochastic demand, local search, genetic algorithm.

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Authors: Zhang Yan, Yu Bin

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Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

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Authors: L. Basha, E. Gjika

Abstract:

This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.

Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: Speech recognition, acoustic phonetic, artificial intelligence, Hidden Markov Models (HMM), statistical models of speech recognition, human machine performance.

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Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

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The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: Input-Output Analysis, Monetary Input-Output Model, Manufacturing Process, Laptop Computer.

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Authors: Jeeeun Kim, Sungjoo Lee

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This research proposes a methodology for patent-citation-based technology input-output analysis by applying the patent information to input-output analysis developed for the dependencies among different industries. For this analysis, a technology relationship matrix and its components, as well as input and technology inducement coefficients, are constructed using patent information. Then, a technology inducement coefficient is calculated by normalizing the degree of citation from certain IPCs to the different IPCs (International patent classification) or to the same IPCs. Finally, we construct a Dependency Structure Matrix (DSM) based on the technology inducement coefficient to suggest a useful application for this methodology.

Keywords: Technology spillover effect, technology relationship, IO table, technology inducement coefficients, patent analysis, patent citation.

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Authors: A. Khourgami, M. Rafiee, H. Jafari, Z. Bitarafan

Abstract:

To study the effect of suitable methods for propagation of True Potato Seed (TPS) progenies, transplant and selection of the best progenies, a factorial experiment base on a randomized complete block design was carried out in the research field of Sahneh region, Kermanshah, Iran during 2009-2010. Five selective progenies from CIP (International Potato Center) including CIP.994013, CIP.994002, CIP.994014, CIP.888006, and CIP.994001 and two transplant preparation methods (Paper pot preparation for mechanical cultivation and preparation in transplant trays for manual cultivation) were studied in three replications. Results showed that different progenies had no significant effect on plant height (cm) and tuber yield (t ha-1), whereas had a significant effect on number of tubers per unit area (m2). There was significant difference between transplant preparation methods for plant height and tuber yield. The interaction effect of progenies and transplant preparation method was not significant for these traits. CIP.888006 progeny and paper pot preparation method produced the highest tuber yields. Also CIP.994002 and CIP.994014 progenies considered as the best progenies under paper pot preparation method due to high yields.

Keywords: Potato, Solanum tuberosum, TPS progenies, Transplant preparation method

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Authors: Tsolmon Tumenjargal, Muhammad Hassan Khalil, Wu Yao Guo

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The research on the effectiveness of environmental assessment (EA) is a milestone effort to evaluate the state of the field, including many contributors related with a lot of countries since more than two decades. In the 1960s, there was a surge of interest between modern industrialized countries over unexpected opposite effects of technical invention. The interest led to choice of approaches for assessing and prediction the impressions of technology and advancement for social and economic, state health and safety, solidity and the circumstances. These are consisting of risk assessment, technology assessment, environmental impact assessment and costbenefit analysis. In this research contribution, the authors have described the research status for environmental assessment in cumulative environmental system. This article discusses the methods for cumulative effect assessment (CEA).

Keywords: Cumulative effect assessment, Environmental impact assessment.

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Authors: Chunling Cong, Chris.P.Tsokos

Abstract:

The objective of the present research manuscript is to perform parametric, nonparametric, and decision tree analysis to evaluate two treatments that are being used for breast cancer patients. Our study is based on utilizing real data which was initially used in “Tamoxifen with or without breast irradiation in women of 50 years of age or older with early breast cancer" [1], and the data is supplied to us by N.A. Ibrahim “Decision tree for competing risks survival probability in breast cancer study" [2]. We agree upon certain aspects of our findings with the published results. However, in this manuscript, we focus on relapse time of breast cancer patients instead of survival time and parametric analysis instead of semi-parametric decision tree analysis is applied to provide more precise recommendations of effectiveness of the two treatments with respect to reoccurrence of breast cancer.

Keywords: decision tree, breast cancer treatments, parametricanalysis, non-parametric analysis

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Authors: Bita Mashayekhi, Mohammad Ara

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The purpose of this study is to provide some empirical evidence about implementing Activity-Based Costing (ABC) in the hospitality industry in Iran. For this purpose, we consider the Tabriz International Hotel as our sample hotel and then gather the relevant data from its cost accounting system in 2012. Then, we use ABC as our costing method and compare the cost of each service unit with that cost which had been extracted for the traditional costing method. The results show a different cost per unit for two methods. Also, because of its more precise and detailed provided information, an ABC system facilitates the decision-making process for managers on decisions related to profitability analysis, budgeting, pricing, and so on.

Keywords: Activity-based costing, activity, cost driver, hospitality industry.

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Authors: Thomas Jin-Chee Liu, Ji-Fu Tseng, Yu-Shen Chen

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This paper investigates the thermo-electric effects around the crack and notch tips under the electric current load. The research methods include the finite element analysis and thermal imaging experiment. The finite element solutions show that the electric current density field concentrates at the crack tip. Due to the Joule heating, this electric concentration causes the hot spot at the tip zone. From numerical and experimental results, this hot spot is identified. The temperature of the hot spot is affected by the electric load, operation time and geometry of the sample.

Keywords: Thermo-electric, Joule heating, crack tip, notch tip.

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Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

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Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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Authors: Marcel Rojahn, Edzard Weber, Norbert Gronau

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Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in)consistence for the research field of job-shop scheduling by a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability and combinability of scheduling methods is unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods.

Keywords: Job-shop scheduling, JSP, terminology, notation, standardization.

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Authors: Wei-hua Ai, Wei Yan, Xiang Li

Abstract:

Data compression is used operationally to reduce bandwidth and storage requirements. An efficient method for achieving lossless weather radar data compression is presented. The characteristics of the data are taken into account and the optical linear prediction is used for the PPI images in the weather radar data in the proposed method. The next PPI image is identical to the current one and a dramatic reduction in source entropy is achieved by using the prediction algorithm. Some lossless compression methods are used to compress the predicted data. Experimental results show that for the weather radar data, the method proposed in this paper outperforms the other methods.

Keywords: Lossless compression, weather radar data, optical linear prediction, PPI image

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Authors: Marc Diesse, Hochschule Heilbronn

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We address the question of identifying the configuration space singularities of linkages, i.e., points where the configuration space is not locally a submanifold of Euclidean space. Because the configuration space cannot be smoothly parameterized at such points, these singularity types have a significantly negative impact on the kinematics of the linkage. It is known that Jacobian methods do not provide sufficient conditions for the existence of CS-singularities. Herein, we present several additional algebraic criteria that provide the sufficient conditions. Further, we use those criteria to analyze certain classes of planar linkages. These examples will also show how the presented criteria can be checked using algorithmic methods.

Keywords: Linkages, configuration space singularities, real algebraic geometry, analytic geometry, computer algebra.

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Authors: Walid Aydi, Nouri Masmoudi, Lotfi Kamoun

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Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address the corneal reflection, a novel reflection removal method is proposed in this paper. Comparative experiments of two existing methods for reflection removal method are evaluated on CASIA iris image databases V3. The experimental results reveal that the proposed algorithm provides higher performance in reflection removal.

Keywords: iris, pupil, specular highlights, reflection removal

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Authors: Parul Khanna, Pavol Zavarsky, Dale Lindskog

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Doxing is a term derived from documents, and hence consists of collecting information on an organization or individual through social media websites, search engines, password cracking methods, social engineering tools and other sources of publicly displayed information. The main purpose of doxing attacks is to threaten, embarrass, harass and humiliate the organization or individual. Various tools are used to perform doxing. Tools such as Maltego visualize organization’s architecture which helps in determining weak links within the organization. This paper discusses limitations of Maltego Chlorine CE 3.6.0 and suggests measures as to how organizations can use these tools to protect themselves from doxing attacks.

Keywords: Advanced Persistent Threat, FOCA, OSINT, PII.

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Authors: Soungwan Kim

Abstract:

This study identifies factors underlying the digital divide that is faced by the disabled. The results of its analysis showed that the digital divide in PC use is affected by age, number of years of education, employment status, and household income of more than KRW 3 million. The digital divide in smart device use is affected by sex, age, number of years of education, time when disability struck, and household income of more than KRW 3 million. Based on these results, this study proposes methods for bridging the digital divide faced by the disabled.

Keywords: Digital divide, digital divide for the disabled, information accessibility for pcs and smart devices.

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: Classification, machine learning, time representation, stock prediction.

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Authors: Goh Han Keat, Azman Samsudin Zurinahni Zainol

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The increase popularity of multimedia application especially in image processing places a great demand on efficient data storage and transmission techniques. Network communication such as wireless network can easily be intercepted and cause of confidential information leaked. Unfortunately, conventional compression and encryption methods are too slow; it is impossible to carry out real time secure image processing. In this research, Embedded Zerotree Wavelet (EZW) encoder which specially designs for wavelet compression is examined. With this algorithm, three methods are proposed to reduce the processing time, space and security protection that will be secured enough to protect the data.

Keywords: Embedded Zerotree Wavelet (EZW), Imagecompression, Wavelet encoder, Entropy encoder, Encryption.

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Authors: Mansour Nikpour, Mohsen Ghasemi, Elahe Mosavi, Mohd Zin Kandar

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lack of convenience condition is one of the problems in open spaces in hot and dry regions. Nowadays parks and green landscapes was designed and constructed without any attention to convenience condition. If this process continues, Citizens will encounter with some problems. Harsh climatic condition decreases the efficiency of people-s activities. However there is hard environment condition in hot and dry regions, Convenience condition has been provided in Iranian traditional architecture by using techniques and methods. In this research at the first step characteristics of Iranian garden that can effect on creating sustainable spaces were investigated through observation method. Pleasure space in cities will be created with using these methods and techniques in future cities. Furthermore the comparison between Iranian garden and landscape in today-s cities demonstrate the effectiveness of Iranian garden characteristics on sustainable spaces. Iranian architects used simple and available methods for creating open architectural spaces. In addition desirable conditions were provided with taking in to account both physically and spiritually. Parks and landscapes in future cities can be designed and constructed with respect to architectural techniques that used in Iranian gardens in hot and arid regions.

Keywords: Iranian garden, convenience condition, landscape, sustainable

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Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

Data Envelopment Analysis (DEA) is a methodology that computes efficiency values for decision making units (DMU) in a given period by comparing the outputs with the inputs. In many cases, there are some time lag between the consumption of inputs and the production of outputs. For a long-term research project, it is hard to avoid the production lead time phenomenon. This time lag effect should be considered in evaluating the performance of organizations. This paper suggests a model to calculate efficiency values for the performance evaluation problem with time lag. In the experimental part, the proposed methods are compared with the CCR and an existing time lag model using the data set of the 21st century frontier R&D program which is a long-term national R&D program of Korea.

Keywords: DEA, Efficiency, Time Lag

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Authors: Ghada Badr, Arwa Alturki

Abstract:

The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: Alignment, RNA secondary structure, pairwise, component-based, data mining.

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Authors: Zeinab Ghasemi, S. Amirhassan Monadjemi, Abbas Vafaei

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This paper presents a comparative analysis of a new unsupervised PCA-based technique for steel plates texture segmentation towards defect detection. The proposed scheme called Variance Based Component Analysis or VBCA employs PCA for feature extraction, applies a feature reduction algorithm based on variance of eigenpictures and classifies the pixels as defective and normal. While the classic PCA uses a clusterer like Kmeans for pixel clustering, VBCA employs thresholding and some post processing operations to label pixels as defective and normal. The experimental results show that proposed algorithm called VBCA is 12.46% more accurate and 78.85% faster than the classic PCA.

Keywords: Principal Component Analysis; Variance Based Component Analysis; Defect Detection; Texture Segmentation.

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Authors: Lalit Garg, Sally McClean, Maria Barton

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Healthcare issues continue to pose huge problems and incur massive costs. As a result there are many challenging problems still unresolved. In this paper, we will carry out an extensive scientific survey of different areas of management and planning in an attempt to identify where there has already been a substantial contribution from management science methods to healthcare problems and where there is a clear potential for more work to be done. The focus will be on the read-across to the healthcare domain from such approaches applied generally to management and planning and how the methods can be used to improvement patient care. We conclude that, since the healthcare domain significantly differs from traditional areas of management and planning, in some cases there is a need to modify the approaches so as to incorporate the complexities of healthcare, and fully exploit the potential for improvement.

Keywords: Management science, management and planning, transforming services, healthcare.

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Authors: Vitalice K. Oduol

Abstract:

The paper considers a single-server queue with fixedsize batch Poisson arrivals and exponential service times, a model that is useful for a buffer that accepts messages arriving as fixed size batches of packets and releases them one packet at time. Transient performance measures for queues have long been recognized as being complementary to the steady-state analysis. The focus of the paper is on the use of the functions that arise in the analysis of the transient behaviour of the queuing system. The paper exploits practical modelling to obtain a solution to the integral equation encountered in the analysis. Results obtained indicate that under heavy load conditions, there is significant disparity in the statistics between the transient and steady state values.

Keywords: batch arrivals, modelling, single-server queue, time-varying probabilities, transient analysis.

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