Search results for: microarray data analysis.

Authors: T. Yamaguchi, M. Watanabe, M. Sasajima, C. Yuan, S. Maruyama, T. B. Ibrahim, H. Tomita

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This paper deals with nonlinear vibration analysis using finite element method for frame structures consisting of elastic and viscoelastic damping layers supported by multiple nonlinear concentrated springs with hysteresis damping. The frame is supported by four nonlinear concentrated springs near the four corners. The restoring forces of the springs have cubic non-linearity and linear component of the nonlinear springs has complex quantity to represent linear hysteresis damping. The damping layer of the frame structures has complex modulus of elasticity. Further, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled differential equations using normal coordinate corresponding to linear natural modes. Comparing shares of strain energy of the elastic frame, the damping layer and the springs, we evaluate the influences of the damping couplings on the linear and nonlinear impact responses. We also investigate influences of damping changed by stiffness of the elastic frame on the nonlinear coupling in the damped impact responses.

Keywords: Dynamic response, Nonlinear impact response, Finite Element analysis, Numerical analysis.

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Authors: Roslinda Nazar, Amin Noor, Khamisah Jafar, Ioan Pop

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In this paper, the steady laminar three-dimensional boundary layer flow and heat transfer of a copper (Cu)-water nanofluid in the vicinity of a permeable shrinking flat surface in an otherwise quiescent fluid is studied. The nanofluid mathematical model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Dual solutions (upper and lower branch solutions) are found for the similarity boundary layer equations for a certain range of the suction parameter. A stability analysis has been performed to show which branch solutions are stable and physically realizable. The numerical results for the skin friction coefficient and the local Nusselt number as well as the velocity and temperature profiles are obtained, presented and discussed in detail for a range of various governing parameters.

Keywords: Heat Transfer, Nanofluid, Shrinking Surface, Stability Analysis, Three-Dimensional Flow.

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Authors: Ágnes Vathy-Fogarassy, Balázs Feil, János Abonyi

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Most of fuzzy clustering algorithms have some discrepancies, e.g. they are not able to detect clusters with convex shapes, the number of the clusters should be a priori known, they suffer from numerical problems, like sensitiveness to the initialization, etc. This paper studies the synergistic combination of the hierarchical and graph theoretic minimal spanning tree based clustering algorithm with the partitional Gath-Geva fuzzy clustering algorithm. The aim of this hybridization is to increase the robustness and consistency of the clustering results and to decrease the number of the heuristically defined parameters of these algorithms to decrease the influence of the user on the clustering results. For the analysis of the resulted fuzzy clusters a new fuzzy similarity measure based tool has been presented. The calculated similarities of the clusters can be used for the hierarchical clustering of the resulted fuzzy clusters, which information is useful for cluster merging and for the visualization of the clustering results. As the examples used for the illustration of the operation of the new algorithm will show, the proposed algorithm can detect clusters from data with arbitrary shape and does not suffer from the numerical problems of the classical Gath-Geva fuzzy clustering algorithm.

Keywords: Clustering, fuzzy clustering, minimal spanning tree, cluster validity, fuzzy similarity.

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Authors: Brittany E. Coff, Tommy K. K. Ngai, Laura A. S. MacDonald

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Many organizations in the Water, Sanitation and Hygiene (WASH) sector provide education and training in order to increase the effectiveness of their WASH interventions. A key challenge for these organizations is measuring how well their education and training activities contribute to WASH improvements. It is crucial for implementers to understand the returns of their education and training activities so that they can improve and make better progress toward the desired outcomes. This paper presents information on CAWST’s development and piloting of the evaluation methodology. The Centre for Affordable Water and Sanitation Technology (CAWST) has developed a methodology for evaluating education and training activities, so that organizations can understand the effectiveness of their WASH activities and improve accordingly. CAWST developed this methodology through a series of research partnerships, followed by staged field pilots in Nepal, Peru, Ethiopia and Haiti. During the research partnerships, CAWST collaborated with universities in the UK and Canada to: review a range of available evaluation frameworks, investigate existing practices for evaluating education activities, and develop a draft methodology for evaluating education programs. The draft methodology was then piloted in three separate studies to evaluate CAWST’s, and CAWST’s partner’s, WASH education programs. Each of the pilot studies evaluated education programs in different locations, with different objectives, and at different times within the project cycles. The evaluations in Nepal and Peru were conducted in 2013 and investigated the outcomes and impacts of CAWST’s WASH education services in those countries over the past 5-10 years. In 2014, the methodology was applied to complete a rigorous evaluation of a 3-day WASH Awareness training program in Ethiopia, one year after the training had occurred. In 2015, the methodology was applied in Haiti to complete a rapid assessment of a Community Health Promotion program, which informed the development of an improved training program. After each pilot evaluation, the methodology was reviewed and improvements were made. A key concept within the methodology is that in order for training activities to lead to improved WASH practices at the community level, it is not enough for participants to acquire new knowledge and skills; they must also apply the new skills and influence the behavior of others following the training. The steps of the methodology include: development of a Theory of Change for the education program, application of the Kirkpatrick model to develop indicators, development of data collection tools, data collection, data analysis and interpretation, and use of the findings for improvement. The methodology was applied in different ways for each pilot and was found to be practical to apply and adapt to meet the needs of each case. It was useful in gathering specific information on the outcomes of the education and training activities, and in developing recommendations for program improvement. Based on the results of the pilot studies, CAWST is developing a set of support materials to enable other WASH implementers to apply the methodology. By using this methodology, more WASH organizations will be able to understand the outcomes and impacts of their training activities, leading to higher quality education programs and improved WASH outcomes.

Keywords: Education and training, capacity building, evaluation, water and sanitation.

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: Audit fee, heteroscedasticity, Lagrange multiplier test, periodicity.

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Authors: Carolina B. Baguio

Abstract:

One of the purposes of the robust method of estimation is to reduce the influence of outliers in the data, on the estimates. The outliers arise from gross errors or contamination from distributions with long tails. The trimmed mean is a robust estimate. This means that it is not sensitive to violation of distributional assumptions of the data. It is called an adaptive estimate when the trimming proportion is determined from the data rather than being fixed a “priori-. The main objective of this study is to find out the robustness properties of the adaptive trimmed means in terms of efficiency, high breakdown point and influence function. Specifically, it seeks to find out the magnitude of the trimming proportion of the adaptive trimmed mean which will yield efficient and robust estimates of the parameter for data which follow a modified Weibull distribution with parameter λ = 1/2 , where the trimming proportion is determined by a ratio of two trimmed means defined as the tail length. Secondly, the asymptotic properties of the tail length and the trimmed means are also investigated. Finally, a comparison is made on the efficiency of the adaptive trimmed means in terms of the standard deviation for the trimming proportions and when these were fixed a “priori". The asymptotic tail lengths defined as the ratio of two trimmed means and the asymptotic variances were computed by using the formulas derived. While the values of the standard deviations for the derived tail lengths for data of size 40 simulated from a Weibull distribution were computed for 100 iterations using a computer program written in Pascal language. The findings of the study revealed that the tail lengths of the Weibull distribution increase in magnitudes as the trimming proportions increase, the measure of the tail length and the adaptive trimmed mean are asymptotically independent as the number of observations n becomes very large or approaching infinity, the tail length is asymptotically distributed as the ratio of two independent normal random variables, and the asymptotic variances decrease as the trimming proportions increase. The simulation study revealed empirically that the standard error of the adaptive trimmed mean using the ratio of tail lengths is relatively smaller for different values of trimming proportions than its counterpart when the trimming proportions were fixed a 'priori'.

Keywords: Adaptive robust estimate, asymptotic efficiency, breakdown point, influence function, L-estimates, location parameter, tail length, Weibull distribution.

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Authors: Susmita Sahoo, Madhumanti Datta, Rajib Kar

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This work proposes an accurate crosstalk noise estimation method in the presence of multiple RLC lines for the use in design automation tools. This method correctly models the loading effects of non switching aggressors and aggressor tree branches using resistive shielding effect and realistic exponential input waveforms. Noise peak and width expressions have been derived. The results obtained are at good agreement with SPICE results. Results show that average error for noise peak is 4.7% and for the width is 6.15% while allowing a very fast analysis.

Keywords: Crosstalk, distributed RLC segments, On-Chip interconnect, output response, VLSI, noise peak, noise width.

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: Classifier ensemble, breast cancer survivability, data mining, SEER.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

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This paper presents design trade-off and performance impacts of the amount of pipeline phase of control path signals in a wormhole-switched network-on-chip (NoC). The numbers of the pipeline phase of the control path vary between two- and one-cycle pipeline phase. The control paths consist of the routing request paths for output selection and the arbitration paths for input selection. Data communications between on-chip routers are implemented synchronously and for quality of service, the inter-router data transports are controlled by using a link-level congestion control to avoid lose of data because of an overflow. The trade-off between the area (logic cell area) and the performance (bandwidth gain) of two proposed NoC router microarchitectures are presented in this paper. The performance evaluation is made by using a traffic scenario with different number of workloads under 2D mesh NoC topology using a static routing algorithm. By using a 130-nm CMOS standard-cell technology, our NoC routers can be clocked at 1 GHz, resulting in a high speed network link and high router bandwidth capacity of about 320 Gbit/s. Based on our experiments, the amount of control path pipeline stages gives more significant impact on the NoC performance than the impact on the logic area of the NoC router.

Keywords: Network-on-Chip, Synchronous Parallel Pipeline, Router Architecture, Wormhole Switching

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Authors: M. Glomski, M. Lopes

Abstract:

Seemingly simple probabilities in the m-player game bingo have never been calculated. These probabilities include expected game length and the expected number of winners on a given turn. The difficulty in probabilistic analysis lies in the subtle interdependence among the m-many bingo game cards in play. In this paper, the game i got it!, a bingo variant, is considered. This variation provides enough weakening of the inter-player dependence to allow probabilistic analysis not possible for traditional bingo. The probability of winning in exactly k turns is calculated for a one-player game. Given a game of m-many players, the expected game length and tie probability are calculated. With these calculations, the game-s interesting payout scheme is considered.

Keywords: Conditional probability, games of chance, npersongames, probability theory.

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Authors: Mohammed Erritali

Abstract:

The growth in the volume of text data such as books and articles in libraries for centuries has imposed to establish effective mechanisms to locate them. Early techniques such as abstraction, indexing and the use of classification categories have marked the birth of a new field of research called "Information Retrieval". Information Retrieval (IR) can be defined as the task of defining models and systems whose purpose is to facilitate access to a set of documents in electronic form (corpus) to allow a user to find the relevant ones for him, that is to say, the contents which matches with the information needs of the user. Most of the models of information retrieval use a specific data structure to index a corpus which is called "inverted file" or "reverse index". This inverted file collects information on all terms over the corpus documents specifying the identifiers of documents that contain the term in question, the frequency of each term in the documents of the corpus, the positions of the occurrences of the word... In this paper we use an oriented object database (db4o) instead of the inverted file, that is to say, instead to search a term in the inverted file, we will search it in the db4o database. The purpose of this work is to make a comparative study to see if the oriented object databases may be competing for the inverse index in terms of access speed and resource consumption using a large volume of data.

Keywords: Information Retrieval, indexation, oriented object database (db4o), inverted file.

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Authors: Taweepol Suesut, Arjin Numsomran, Vittaya Tipsuwanporn

Abstract:

This paper presents the communication network for machine vision system to implement to control systems and logistics applications in industrial environment. The real-time distributed over the network is very important for communication among vision node, image processing and control as well as the distributed I/O node. A robust implementation both with respect to camera packaging and data transmission has been accounted. This network consists of a gigabit Ethernet network and a switch with integrated fire-wall is used to distribute the data and provide connection to the imaging control station and IEC-61131 conform signal integration comprising the Modbus TCP protocol. The real-time and delay time properties each part on the network were considered and worked out in this paper.

Keywords: Distributed Real-Time Automation, Machine Visionand Ethernet.

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Authors: Panpan Xu, Qiying Zhang, Hui Qian

Abstract:

Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K⁺, Na⁺, Mg²⁺, Ca²⁺, SO₄^2-, Cl^-, HCO₃^-, and CO₃^2-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl^-, Na⁺, Mg²⁺, and SO₄^2-, and the HCO₃^- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.

Keywords: Irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process.

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Authors: Charbel Geryes Aoun, Loic Lagadec

Abstract:

A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g. Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple-views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: Smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS.

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Authors: Ahmad M. Sarhan, Omar I. Al Helalat

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In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.

Keywords: ANN, Backpropagation, Gaussian, LMS, MSE, Neuron, standard deviation, Widrow-Hoff rule.

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Authors: I. Jafari, A. Ershadi, E. Najafpour, N. Hedayat

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Energy and exergy study of air-water combined solar collector which is called dual purpose solar collector (DPSC) is investigated. The method of ε - NTU is used. Analysis is performed for triangle channels. Parameters like the air flow rate and water inlet temperature are studied. Results are shown that DPSC has better energy and exergy efficiency than single collector. In addition, the triangle passage with water inlet temperature of 60O C has shown better exergy and energy efficiency.

Keywords: Efficiency, Exergy, Irreversibility, Solar collector.

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Authors: Racha Khairallah, Lamia Ben Hamida

Abstract:

Our paper attempts to examine how Swiss manufacturing firms manage to learn from patent citations to improve their innovation performance. We argue that the assessment of these effects needs a detailed analysis of spillovers according to the source of knowledge with respect to formal and informal patent citations made in European and internal search, the horizontal and vertical mechanisms by which knowledge spillovers take place, and the technological characteristics of innovative firms that able them to absorb external knowledge and integrate it in their existing innovation process. We use Organisation for Economic Co-operation and Development (OECD) data and find evidence that knowledge spillovers occur only from horizontal and backward linkages. The importance of these effects depends on the type of citation, in which the references to non-patent literature (informal citations made in European and international searches) have a greater impact. In addition, only firms with high technological capacities benefit from knowledge spillovers from formal and informal citations. Low-technology firms fail to catch up and efficiently learn external knowledge from patent citations.

Keywords: Innovation performance, patent citation, absorptive capacity, knowledge spillover mechanisms.

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Authors: Wai-Sum Lee

Abstract:

This study investigates C-V and V-C co-articulation in Cantonese monosyllables of the CV, VC or CVC structure, with C = one of the three stop consonants [p, t, k] and V = one of the three corner vowels [i, a, u]. Five repetitions of each test syllable on a randomized list were elicited from Cantonese young adult speakers in their early-20s. A research tool, EMA AG500, was used to record the synchronized audio signals and articulatory data at three different locations of the tongue – tongue tip, tongue middle, and tongue back – and the positions of the upper and lower lips during the test syllables. The main findings based on the articulatory data collected from two male Cantonese speakers are as follows: (i) For the syllable-initial [p-], strong co-articulation is observed when [p-] preceding the high vowel [i] or [u], but not the low vowel [a]. As for the syllable-final [-p], it is strongly co-articulated with the preceding vowel, even when the vowel is [a]. (ii) The co-articulation between the initial [t-] and the following vowel of any type is weak. In the syllable-final position, the degree of co-articulatory resistance of [-t] is also large when following the vowel [u], but [-t] is largely co-articulated with the preceding vowel when the vowel is [i] or [a]. (iii) The strength of co-articulation differs when the initial [k-] precedes the different types of vowel. A stronger co-articulation between [k-] and [i] than between [k-] and [u], and the strength of co-articulation is much reduced between [k-] and [a]. However, in the syllable-final position, there is strong co-articulation between [-k] and the preceding vowel [a]. (iv) Among the three types of stop consonants in the syllable-initial position, the decreasing degree of co-articulatory resistance (CR) is [t-] > [k-] > [p-], and the degree of CR is reduced during all three types of stop in the syllable-final position. In general, the data on co-articulation between consonant and vowel in the Cantonese monosyllables are similar to those in other languages reported in previous studies.

Keywords: Cantonese, co-articulation, consonant, vowel.

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Authors: Walter Sebron, Hans Tschürtz, Peter Krebs

Abstract:

The choice of applicable analysis methods in safety or systems engineering depends on the depth of knowledge about a system, and on the respective lifecycle phase. However, the analysis method chain still shows gaps as it should support system analysis during the lifecycle of a system from a rough concept in pre-project phase until end-of-life. This paper’s goal is to discuss an analysis method, the VISSE Shell Model Analysis (VISMA) method, which aims at closing the gap in the early system lifecycle phases, like the conceptual or pre-project phase, or the project start phase. It was originally developed to aid in the definition of the system boundary of electronic system parts, like e.g. a control unit for a pump motor. Furthermore, it can be also applied to non-electronic system parts. The VISMA method is a graphical sketch-like method that stratifies a system and its parts in inner and outer shells, like the layers of an onion. It analyses a system in a two-step approach, from the innermost to the outermost components followed by the reverse direction. To ensure a complete view of a system and its environment, the VISMA should be performed by (multifunctional) development teams. To introduce the method, a set of rules and guidelines has been defined in order to enable a proper shell build-up. In the first step, the innermost system, named system under consideration (SUC), is selected, which is the focus of the subsequent analysis. Then, its directly adjacent components, responsible for providing input to and receiving output from the SUC, are identified. These components are the content of the first shell around the SUC. Next, the input and output components to the components in the first shell are identified and form the second shell around the first one. Continuing this way, shell by shell is added with its respective parts until the border of the complete system (external border) is reached. Last, two external shells are added to complete the system view, the environment and the use case shell. This system view is also stored for future use. In the second step, the shells are examined in the reverse direction (outside to inside) in order to remove superfluous components or subsystems. Input chains to the SUC, as well as output chains from the SUC are described graphically via arrows, to highlight functional chains through the system. As a result, this method offers a clear and graphical description and overview of a system, its main parts and environment; however, the focus still remains on a specific SUC. It helps to identify the interfaces and interfacing components of the SUC, as well as important external interfaces of the overall system. It supports the identification of the first internal and external hazard causes and causal chains. Additionally, the method promotes a holistic picture and cross-functional understanding of a system, its contributing parts, internal relationships and possible dangers within a multidisciplinary development team.

Keywords: Analysis methods, functional safety, hazard identification, system and safety engineering, system boundary definition, system safety.

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Authors: R. Ashok Bakkiyaraj, N. Kumarappan

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This paper investigates the suitability of Latin Hypercube sampling (LHS) for composite electric power system reliability analysis. Each sample generated in LHS is mapped into an equivalent system state and used for evaluating the annualized system and load point indices. DC loadflow based state evaluation model is solved for each sampled contingency state. The indices evaluated are loss of load probability, loss of load expectation, expected demand not served and expected energy not supplied. The application of the LHS is illustrated through case studies carried out using RBTS and IEEE-RTS test systems. Results obtained are compared with non-sequential Monte Carlo simulation and state enumeration analytical approaches. An error analysis is also carried out to check the LHS method’s ability to capture the distributions of the reliability indices. It is found that LHS approach estimates indices nearer to actual value and gives tighter bounds of indices than non-sequential Monte Carlo simulation.

Keywords: Composite power system, Latin Hypercube sampling, Monte Carlo simulation, Reliability evaluation, Variance analysis.

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Authors: Meseret Teshome

Abstract:

This study has the objective of assessing the effect of kaizen (5S, Muda elimination and Quality Control Circle (QCC) on employees’ affective attitude (job satisfaction, commitment and job stress) in Kombolcha Textile Share Company. A conceptual model was developed to describe the relationship between Kaizen and Employees’ Affective Attitude (EAA) factors. The three factors of Employee Affective Attitude were measured using questionnaire derived from other validated questionnaire. In the data collection to conduct this study; questionnaire, unstructured interview, written documents and direct observations are used. To analyze the data, SPSS and Microsoft Excel were used. In addition, the internal consistency of similar items in the questionnaire instrument was measured for their equivalence by using the cronbach’s alpha test. In this study, the effect of 5S, Muda elimination and QCC on job satisfaction, commitment and job stress in Kombolcha Textile Share Company is assessed and factors that reduce employees’ job satisfaction with respect to kaizen implementation are identified. The total averages of means from the questionnaire are 3.1 for job satisfaction, 4.31 for job commitment and 4.2 for job stress. And results from interview and secondary data show that kaizen implementation have effect on EAA. In general, based on the thesis results it was concluded that kaizen (5S, muda elimination and QCC) have positive effect for improving EAA factors at KTSC. Finally, recommendations for improvement are given based on the results.

Keywords: Kaizen, job satisfaction, job commitment, job stress.

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Authors: Khaled M. EL-Naggar

Abstract:

This paper presents a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The problem is formulated as an estimation problem. Estimation of the current signal parameters is achieved using a fast and accurate technique. The method is based on discrete dynamic filtering algorithm (DDF). The main advantage of the proposed technique is its ability in producing the estimates in a very short time and at a very high degree of accuracy. The algorithm uses sets of digital samples of the recorded impulse waveform. The proposed technique has been tested using simulated data of practical waveforms. Effects of number of samples and data window size are studied. Results are reported and discussed.

Keywords: Digital Filtering, Estimation, Impulse wave, Stochastic filtering.

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Authors: Fereydoon Sarmadian, Ali Keshavarzi

Abstract:

Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.

Keywords: Artificial neural network, Field capacity, Permanentwilting point, Pedotransfer functions.

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Authors: M. Altekin, R. F. Yükseler

Abstract:

Geometrically nonlinear axisymmetric bending of a shallow spherical shell with a point support at the apex under linearly varying axisymmetric load was investigated numerically. The edge of the shell was assumed to be simply supported or clamped. The solution was obtained by the finite difference and the Newton-Raphson methods. The thickness of the shell was considered to be uniform and the material was assumed to be homogeneous and isotropic. Sensitivity analysis was made for two geometrical parameters. The accuracy of the algorithm was checked by comparing the deflection with the solution of point supported circular plates and good agreement was obtained.

Keywords: Bending, nonlinear, plate, point support, shell.

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Authors: J. Kala, J. Melcher, M. Škaloud, Z. Kala

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In the paper, the results of sensitivity analysis of the influence of initial imperfections on the web stress state of a thinwalled girder are presented. The results of the study corroborate a very good and effective agreement of experiments with theory. Most input random quantities were found experimentally. The change of sensitivity coefficients in dependence on working load value is analysed. The stress was analysed by means of a geometrically and materially non-linear solution by applying the program ANSYS. This research study offers important background for theoretical studies of stability problems, post-critical effects and limit states of thin-walled steel structures.

Keywords: Buckling, Fatigue, Imperfection, Steel, Sensitivity analysis.

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Authors: Young Gi Byun, Yong Huh, Kiyun Yu, Yong Il Kim

Abstract:

Spatial outliers in remotely sensed imageries represent observed quantities showing unusual values compared to their neighbor pixel values. There have been various methods to detect the spatial outliers based on spatial autocorrelations in statistics and data mining. These methods may be applied in detecting forest fire pixels in the MODIS imageries from NASA-s AQUA satellite. This is because the forest fire detection can be referred to as finding spatial outliers using spatial variation of brightness temperature. This point is what distinguishes our approach from the traditional fire detection methods. In this paper, we propose a graph-based forest fire detection algorithm which is based on spatial outlier detection methods, and test the proposed algorithm to evaluate its applicability. For this the ordinary scatter plot and Moran-s scatter plot were used. In order to evaluate the proposed algorithm, the results were compared with the MODIS fire product provided by the NASA MODIS Science Team, which showed the possibility of the proposed algorithm in detecting the fire pixels.

Keywords: Spatial Outlier Detection, MODIS, Forest Fire

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Authors: A. Deswal, N. S. Deora, H. N. Mishra

Abstract:

The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyze spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), Discriminant Factorial Analysis (DFA) and Soft Independent Modelling by Class Analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable countsshowed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20hrs and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.

Keywords: Electronic-nose, bacteriological, shelf-life, classification.

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Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

Here, a new idea to speed up the operation of complex valued time delay neural networks is presented. The whole data are collected together in a long vector and then tested as a one input pattern. The proposed fast complex valued time delay neural networks uses cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically that the number of computation steps required for the presented fast complex valued time delay neural networks is less than that needed by classical time delay neural networks. Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Complex Valued Time Delay Neural Networks, Cross Correlation, Frequency Domain

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Authors: Marko Spasojevic, Ying Hei Chui, Yuxiang Chen

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Increasing the level of exterior insulation in residential buildings is a popular way for improving the thermal characteristic of building enclosure and reducing heat loss. However, the layout and properties of materials composing the wall have a great effect on moisture accumulation within the wall cavity, long-term durability of a wall as well as the structural performance. A one-dimensional hygrothermal modeling has been performed to investigate moisture condensation risks and the drying capacity of standard 2×4 and 2×6 light wood-frame wall assemblies including exterior low-permeance extruded polystyrene (XPS) insulation. The analysis considered two different wall configurations whereby the rigid insulation board was placed either between Oriented Strand Board (OSB) sheathing and the stud or outboard to the structural sheathing. The thickness of the insulation varied between 0 mm and 50 mm and the analysis has been conducted for eight different locations in Canada, covering climate zone 4 through zone 8. Results show that the wall configuration with low-permeance insulation inserted between the stud and OSB sheathing accumulates more moisture within the stud cavity, compared to the assembly with the same insulation placed exterior to the sheathing. On the other hand, OSB moisture contents of the latter configuration were markedly higher. Consequently, the analysis of hygrothermal performance investigated and compared moisture accumulation in both the OSB and stud cavity. To investigate the structural performance of the wall and the effect of soft insulation layer inserted between the sheathing and framing, forty nail connection specimens were tested. Results have shown that both the connection strength and stiffness experience a significant reduction as the insulation thickness increases. These results will be compared with results from a full-scale shear wall tests in order to investigate if the capacity of shear walls with insulated sheathing would experience a similar reduction in structural capacities.

Keywords: Hygrothermal analysis, insulated sheathing, moisture performance, nail joints, wood shear wall.

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Authors: N.Poolsawad, C.Kambhampati, J. G. F. Cleland

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In this paper, we investigated the characteristic of a clinical dataseton the feature selection and classification measurements which deal with missing values problem.And also posed the appropriated techniques to achieve the aim of the activity; in this research aims to find features that have high effect to mortality and mortality time frame. We quantify the complexity of a clinical dataset. According to the complexity of the dataset, we proposed the data mining processto cope their complexity; missing values, high dimensionality, and the prediction problem by using the methods of missing value replacement, feature selection, and classification.The experimental results will extend to develop the prediction model for cardiology.

Keywords: feature selection, missing values, classification, clinical dataset, heart failure.

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