Search results for: Random Variable

Authors: Syed Iftekhar Ali, M. S. Islam

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In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary content-addressable memory (TCAM). The proposed scheme isolates the sensing unit of the sense amplifier from the large and variable ML capacitance. It employs feedback in the sense amplifier to successfully detect a match while keeping the ML voltage swing low. This reduced voltage swing results in large energy saving. Simulation performed using 130nm 1.2V CMOS logic shows at least 30% total energy saving in our scheme compared to popular current race (CR) scheme for similar search speed. In terms of speed, dynamic energy, peak power consumption and transistor count our scheme also shows better performance than mismatch-dependant (MD) power allocation technique which also employs feedback in the sense amplifier. Additionally, the implementation of our scheme is simpler than CR or MD scheme because of absence of analog control voltage and programmable delay circuit as have been used in those schemes.

Keywords: content-addressable memory, energy consumption, feedback, peak power, sensing scheme, sense amplifier, ternary.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

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In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: Parameterization, response surface, structure optimization, pressure hull.

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Authors: Hicham Benamirouche, Oum Elkheir Moussi

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The purpose of the study is to examine the dynamics of Algeria’s natural gas exports through the Autoregressive Distributed Lag (ARDL) bounds testing approach with break points. The analysis was carried out for the period from 1967 to 2015. Based on imperfect substitution specification, the ARDL approach reveals a long-run equilibrium relationship between Algeria’s Natural gas exports and their determinant factors (Algeria’s gas reserves, Domestic gas consumption, Europe’s GDP per capita, relative prices, the European gas production and the market share of competitors). All the long-run elasticities estimated are statistically significant with a large impact of domestic factors, which constitute the supply constraints. In short term, the elasticities are statistically significant, and almost comparable to those of the long term. Furthermore, the speed of adjustment towards long-run equilibrium is less than one year because of the little flexibility of the long term export contracts. Two break points have been estimated when we employ the domestic gas consumption as a break variable; 1984 and 2010, which reflect the arbitration policy between the domestic gas market and gas exports.

Keywords: Natural gas exports, elasticity, ARDL bounds testing, break points, Algeria.

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Authors: Hui-Chuan Lu

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

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

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Authors: Vikas Tewari, K.R. Pardasani

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Calcium is very important for communication among the neurons. It is vital in a number of cell processes such as secretion, cell movement, cell differentiation. To reduce the system of reactiondiffusion equations of [Ca2+] into a single equation, two theories have been proposed one is excess buffer approximation (EBA) other is rapid buffer approximation (RBA). The RBA is more realistic than the EBA as it considers both the mobile and stationary endogenous buffers. It is valid near the mouth of the channel. In this work we have studied the effects of different types of buffers on calcium diffusion under RBA. The novel thing studied is the effect of sodium ions on calcium diffusion. The model has been made realistic by considering factors such as variable [Ca2+], [Na+] sources, sodium-calcium exchange protein(NCX), Sarcolemmal Calcium ATPase pump. The proposed mathematical leads to a system of partial differential equations which has been solved numerically to study the relationships between different parameters such as buffer concentration, buffer disassociation rate, calcium permeability. We have used Forward Time Centred Space (FTCS) approach to solve the system of partial differential equations.

Keywords: rapid buffer approximation, sodium-calcium exchangeprotein, Sarcolemmal Calcium ATPase pump, buffer disassociationrate, forward time centred space.

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Authors: M. Govindarajan, R. M.Chandrasekaran

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Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

Keywords: Text Data Mining, Comparative Cross-validation, Radial Basis Function, runtime, accuracy.

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Authors: Lokesh Varshney, R. K. Saket

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This paper presents reliability indices evaluation of the rotor core magnetization of the induction motor operated as a self excited induction generator by using probability distribution approach and Monte Carlo simulation. Parallel capacitors with calculated minimum capacitive value across the terminals of the induction motor operated as a SEIG with unregulated shaft speed have been connected during the experimental study. A three phase, 4 poles, 50Hz, 5.5 hp, 12.3A, 230V induction motor coupled with DC Shunt Motor was tested in the electrical machine laboratory with variable reactive loads. Based on this experimental study, it is possible to choose a reliable induction machines operated as a SEIG for unregulated renewable energy application in remote area or where grid is not available. Failure density function, cumulative failure distribution function, survivor function, hazard model, probability of success and probability of failure for reliability evaluation of the three phase induction motor operating as a SEIG have been presented graphically in this paper.

Keywords: Residual magnetism, magnetization curve, induction motor, self excited induction generator, probability distribution, Monte Carlo simulation.

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Authors: Hyun Ah Yoon, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

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Reinforced concrete (RC) shear wall system of residential buildings is popular in South Korea. RC walls are subjected to axial forces in common and the effect of axial forces on the strength loss of the fire damaged walls has not been investigated. This paper aims at investigating temperature distribution on fire damaged concrete walls having different axial loads. In the experiments, a variable of specimens is axial force ratio. RC walls are fabricated with 150mm of wall thicknesses, 750mm of lengths and 1,300mm of heights having concrete strength of 24MPa. After curing, specimens are heated on one surface with ISO-834 standard time-temperature curve for 2 hours and temperature distributions during the test are measured using thermocouples inside the walls. The experimental results show that the temperature of the RC walls exposed to fire increases as axial force ratio increases. To verify the experiments, finite element (FE) models are generated for coupled temperature-structure analyses. The analytical results of thermal behaviors are in good agreement with the experimental results. The predicted displacement of the walls decreases when the axial force increases. 

Keywords: Axial force ratio, coupled analysis, fire, reinforced concrete wall, temperature distribution.

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Authors: Federico Pérez González, Iñaki Goiricelaia Ordorika, Pedro Iriondo Bengoa

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A new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuoustone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different levels of importance from which the bit stream will be generated. The subcomponents of each level of importance are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several enhance levels.

Keywords: Image compression, wavelet transform, highlyscalable, reversible transform, embedded, subcomponents.

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.

Keywords: Tourist, expenses, indexes, statistics, analysis.

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Authors: Dayang Nailul Munna Abang Abdullah, Francine Rozario

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The main objectives of this study were to identify attributes that influence customer satisfaction and determine their relationships with customer satisfaction. The variables included in this research are place/ambience, food quality and service quality as independent variables and customer satisfaction as the dependent variable. A survey questionnaire which consisted of three parts to measure demographic factors, independent variables, and dependent variables was constructed based on items determined by past research. 149 respondents from one of the well known hotel in Kuala Lumpur, MALAYSIA were selected as a sample. Psychometric testing was conducted to determine the reliability and validity of the questionnaire. From the findings, there were positive significant relationship between place/ambience (r=0.563**, p=0.000) and service quality (r=0.544**, p=0.000) with customer satisfaction. However, although relationship between food quality and customer satisfaction was significant, it was in the negative direction (r=- 0.268**, p=0.001). New findings were discovered after conducting this research and previous research findings were strengthened by the results of this research. Future researchers could concentrate on determining attributes that influence customer satisfaction when cost/price is not a factor and reasons for place/ambience is currently becoming the leading factor in determining customer satisfaction.

Keywords: Ambience, Customer Satisfaction, Food Quality, Service Quality.

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: Social network analysis, information diffusion, personality and values, Twitter Mentions Network.

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Authors: Zayed N. Alsulami, Asma F. Aldosseri, Ahmed S. Ezziden, Abdulrahman K. Alonazi

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Children are more susceptible to medication errors than adults. Medication administration process is the last stage in the medication treatment process and most of the errors detected in this stage. Little research has been undertaken about medication errors in children in the Middle East countries. This study was aimed to evaluate how the paediatric nurses adhere to the medication administration policy and also to identify any medication preparation and administration errors or any risk factors. An observational, prospective study of medication administration process from when the nurses preparing patient medication until administration stage (May to August 2014) was conducted in Saudi Arabia. Twelve paediatric nurses serving 90 paediatric patients were observed. 456 drug administered doses were evaluated. Adherence rate was variable in 7 steps out of 16 steps. Patient allergy information, dose calculation, drug expiry date were the steps in medication administration with lowest adherence rates. 63 medication preparation and administration errors were identified with error rate 13.8% of medication administrations. No potentially life-threating errors were witnessed. Few logistic and administrative factors were reported. The results showed that the medication administration policy and procedure need an urgent revision to be more sensible for nurses in practice. Nurses’ knowledge and skills regarding to the medication administration process should be improved.

Keywords: Double checking, Medication administration errors, Medication safety, Nurses.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: Muhamad Nugraha

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Economic growth always correlate positively with the magnitude of the unemployment rate. This is caused by labor which one of important variable to keep growth in the real sector of the region. Meanwhile, the economic structure in districts of Jember showed an increase of economic activity began to shift towards the industrial sector and some other economic sectors, so they have an affects to considerations for policy makers to increase economic growth in Jember as an autonomous region in East Java Province. At the fact, SMEs is among the factors driving economic growth in the region. This is shown by the high amount of SMEs. However, employment in the sector grew slightly slowed. It is caused by a lack of productivity in SMEs. Through the analysis of the transformation of economic structure theory, and the theory of Triple Helix using descriptive analytical method Location Quotient and Shift - Share, found that the results of the economic structure in Jember slowly shifting from the agricultural sector to the industrial sector, because it is dominated by trade sector, hotel and restaurant sector. In addition, SMEs is the potential sector of economic growth in Jember. While to maximizing role and functions of the institution's Research and Development Center of SMEs, there are three points to be known, that are Business Landscape, Business Architecture and Value Added.

Keywords: Economic Growth, SMEs, Labor, Research and Development Center of SMEs.

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Authors: Chih-Ling Huang, Wen-Yi Lin, Kuo-Mo Hsiao

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A method based on the power series solution is proposed to solve the natural frequency of flapping vibration for the rotating inclined Euler beam with constant angular velocity. The vibration of the rotating beam is measured from the position of the corresponding steady state axial deformation. In this paper the governing equations for linear vibration of a rotating Euler beam are derived by the d'Alembert principle, the virtual work principle and the consistent linearization of the fully geometrically nonlinear beam theory in a rotating coordinate system. The governing equation for flapping vibration of the rotating inclined Euler beam is linear ordinary differential equation with variable coefficients and is solved by a power series with four independent coefficients. Substituting the power series solution into the corresponding boundary conditions at two end nodes of the rotating beam, a set of homogeneous equations can be obtained. The natural frequencies may be determined by solving the homogeneous equations using the bisection method. Numerical examples are studied to investigate the effect of inclination angle on the natural frequency of flapping vibration for rotating inclined Euler beams with different angular velocity and slenderness ratio.

Keywords: Flapping vibration, Inclination angle, Natural frequency, Rotating beam.

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Authors: Eisa Noveiri, Adel Taheri Nia

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The Non-Rotating Adjustable Stabilizer / Directional Solution (NAS/DS) is the imitation of a mechanical process or an object by a directional drilling operation that causes a respond mathematically and graphically to data and decision to choose the best conditions compared to the previous mode. The NAS/DS Auto Guide rotary steerable tool is undergoing final field trials. The point-the-bit tool can use any bit, work at any rotating speed, work with any MWD/LWD system, and there is no pressure drop through the tool. It is a fully closed-loop system that automatically maintains a specified curvature rate. The Non–Rotating Adjustable stabilizer (NAS) can be controls curvature rate by exactly positioning and run with the optimum bit, use the most effective weight (WOB) and rotary speed (RPM) and apply all of the available hydraulic energy to the bit. The directional simulator allowed to specify the size of the curvature rate performance errors of the NAS tool and the magnitude of the random errors in the survey measurements called the Directional Solution (DS). The combination of these technologies (NAS/DS) will provide smoother bore holes, reduced drilling time, reduced drilling cost and incredible targeting precision. This simulator controls curvature rate by precisely adjusting the radial extension of stabilizer blades on a near bit Non-Rotating Stabilizer and control process corrects for the secondary effects caused by formation characteristics, bit and tool wear, and manufacturing tolerances.

Keywords: non-rotating, Adjustable stabilizer, simulator, Directional Drilling, optimization, Oil Well Drilling

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Authors: L. L. Ivy-Yap, H. A. Bekhet

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As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationarity of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modelled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO₂ emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: Co-integration, Elasticity, Granger causality, Malaysia, Residential electricity consumption.

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Authors: Rohitash Chandra, Christian W. Omlin

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We present a hybrid architecture of recurrent neural networks (RNNs) inspired by hidden Markov models (HMMs). We train the hybrid architecture using genetic algorithms to learn and represent dynamical systems. We train the hybrid architecture on a set of deterministic finite-state automata strings and observe the generalization performance of the hybrid architecture when presented with a new set of strings which were not present in the training data set. In this way, we show that the hybrid system of HMM and RNN can learn and represent deterministic finite-state automata. We ran experiments with different sets of population sizes in the genetic algorithm; we also ran experiments to find out which weight initializations were best for training the hybrid architecture. The results show that the hybrid architecture of recurrent neural networks inspired by hidden Markov models can train and represent dynamical systems. The best training and generalization performance is achieved when the hybrid architecture is initialized with random real weight values of range -15 to 15.

Keywords: Deterministic finite-state automata, genetic algorithm, hidden Markov models, hybrid systems and recurrent neural networks.

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Authors: R.S.Sabeenian, V.Palanisamy

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Texture classification is a trendy and a catchy technology in the field of texture analysis. Textures, the repeated patterns, have different frequency components along different orientations. Our work is based on Texture Classification and its applications. It finds its applications in various fields like Medical Image Classification, Computer Vision, Remote Sensing, Agricultural Field, and Textile Industry. Weed control has a major effect on agriculture. A large amount of herbicide has been used for controlling weeds in agriculture fields, lawns, golf courses, sport fields, etc. Random spraying of herbicides does not meet the exact requirement of the field. Certain areas in field have more weed patches than estimated. So, we need a visual system that can discriminate weeds from the field image which will reduce or even eliminate the amount of herbicide used. This would allow farmers to not use any herbicides or only apply them where they are needed. A machine vision precision automated weed control system could reduce the usage of chemicals in crop fields. In this paper, an intelligent system for automatic weeding strategy Multi Resolution Combined Statistical & spatial Frequency is used to discriminate the weeds from the crops and to classify them as narrow, little and broad weeds.

Keywords: crop weed discrimination, MRCSF, MRFM, Weeddetection, Spatial Frequency.

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Authors: Jinliang Yuan, Jong-Sung Yu, Bengt Sundén

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A computational fluid dynamics (CFD) model is developed for rechargeable non-aqueous electrolyte lithium-air batteries with a partial opening for oxygen supply to the cathode. Multi-phase transport phenomena occurred in the battery are considered, including dissolved lithium ions and oxygen gas in the liquid electrolyte, solid-phase electron transfer in the porous functional materials and liquid-phase charge transport in the electrolyte. These transport processes are coupled with the electrochemical reactions at the active surfaces, and effects of discharge reaction-generated solid Li2O2 on the transport properties and the electrochemical reaction rate are evaluated and implemented in the model. The predicted results are discussed and analyzed in terms of the spatial and transient distribution of various parameters, such as local oxygen concentration, reaction rate, variable solid Li2O2 volume fraction and porosity, as well as the effective diffusion coefficients. It is found that the effect of the solid Li2O2 product deposited at the solid active surfaces is significant on the transport phenomena and the overall battery performance.

Keywords: Computational Fluid Dynamics (CFD), Modeling, Multi-phase, Transport Phenomena, Lithium-air battery.

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Authors: Chong Wang, Kellem M. Soares, Luis E. Kosteski

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The problem of toughening in brittle materials reinforced by fibers is complex, involving all of the mechanical properties of fibers, matrix and the fiber/matrix interface, as well as the geometry of the fiber. Development of new numerical methods appropriate to toughening simulation and analysis is necessary. In this work, we have performed simulations and analysis of toughening in brittle matrix reinforced by randomly distributed fibers by means of the discrete elements method. At first, we put forward a mechanical model of toughening contributed by random fibers. Then with a numerical program, we investigated the stress, damage and bridging force in the composite material when a crack appeared in the brittle matrix. From the results obtained, we conclude that: (i) fibers of high strength and low elasticity modulus are beneficial to toughening; (ii) fibers of relatively high elastic modulus compared to the matrix may result in substantial matrix damage due to spalling effect; (iii) employment of high-strength synthetic fibers is a good option for toughening. We expect that the combination of the discrete element method (DEM) with the finite element method (FEM) can increase the versatility and efficiency of the software developed. The present work can guide the design of ceramic composites of high performance through the optimization of the parameters.

Keywords: Bridging stress, discrete element method, fiber reinforced composites, toughening.

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: Model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs.

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Authors: Mananya Meenakorn

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This research aims to investigate: (1) Relationship between the quality of working life and organizational commitment of municipal employee in Samut Sakhon Province. (2) To compare the quality of working life and the organizational commitment of municipal employee in Samut Sakhon Province by the gender, age, education, official experience, position, division, and income. This study is a quantitative research; data was collected by questionnaires distributed to the municipal employee in Samut Sakhon province for 241 sample by stratified random sampling. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including t-test, F-test and Pearson correlation for hypothesis testing. Finding showed that the quality of working life and the organizational commitment of municipal Employee in Samut Sakhon province in terms of compensation and fair has a positive correlation (r = 0.673) and the comparison of the quality of working life and organizational commitment of municipal employees in Samut Sakhon province by gender. We found that the overall difference was statistically significant at the 0.05 level and we also found stability and progress in career path and the characteristics are beneficial to society has a difference was statistically significant at the 0.01 level, and the participation and social acceptance has a difference was statistically significant at the 0.05 level.

Keywords: Quality of working life, organizational commitment, municipal employee, Samut Sakhon province.

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Authors: Zahra Lashgari, Naghmeh Sadat MaghamiTekiyeh

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Recent evidences on liquidity and valuation of securities in the capital markets clearly show the importance of stock market liquidity and valuation of firms. In this paper, relationship between transparency, liquidity, and valuation is studied by using data obtained from 70 companies listed in Tehran Stock Exchange during2003-2012. In this study, discriminatory earnings management, as a sign of lack of transparency and Tobin's Q, was used as the criteria of valuation. The results indicate that there is a significant and reversed relationship between earnings management and liquidity. On the other hand, there is a relationship between liquidity and transparency.The results also indicate a significant relationship between transparency and valuation. Transparency has an indirect effect on firm valuation alone or through the liquidity channel. Although the effect of transparency on the value of a firm was reduced by adding the variable of liquidity, the cumulative effect of transparency and liquidity increased.

Keywords: Firm valuation, Earnings management, Liquidity, Tobin's Q, Transparency.

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Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

Abstract:

Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: Dynamic impact, deformable boundary conditions, finite element modeling, FEM, finite element, FE, LS-DYNA, Stainless steel pipe.

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Authors: Adesanya Anuoluwapo Olusola

Abstract:

Technology has moved into the classroom, and it becomes difficult talking of achievement in and attitude to learning without making mention of it. The use of technology makes learning easy, real and practical as it motivates learners, sustains their interest and improves their attitude to learning. This study, therefore examined the pre-service teachers’ assessment of information technology application to instruction. The use of technology emphasizes and encourages active learning in the classroom. The study involved 100 pre-service teachers in the selected two (2) Colleges of Education, Nigeria. Purposive random sampling was used in selecting the participants and ex-post facto design was adopted the in which there is no manipulation of variables. Two valid and reliable instruments were used for data collection: Access Point ICT facilities and Application of ICT. The study established that pre-service teachers have less access to ICT facilities and Application of ICT in the college, apart from those students having the access outside the college. Also fewer pre-service teachers used ICT facilities on weekly and monthly bases. It was concluded that the establishment of students’ resources centres and Campus wide wireless connectivity must be implemented so as to improve and enhance students’ achievement in and attitude to learning. The time and attention devoted to learning activities and strategic specialized ICT skills and requisite entrepreneur skills should be increased so as to have easy access to information sources and be able to apply it in teaching process.

Keywords: Computer, ICT Application, Learning Facilities, Pre-Service Teachers.

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Authors: R.Balamurugan, S.Subramanian

Abstract:

This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.

Keywords: Multiple fuels, power economic dispatch, selfadaptivedifferential evolution and valve-point effects.

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Authors: Jia-Ru Li, Chia-Jung Li, Ching-Wen Lin

Abstract:

Contrary to negative emotion regulation, coping with positive moods have received less attention in adolescent adjustment. However, some research has found that everyone is different on dealing with their positive emotions, which affects their adaptation and well-being. The purpose of the present study was to investigate the relationship between positive emotions dampening and internalizing behavior problems of adolescent in Taiwan. A survey was conducted and 208 students (12 to14 years old) completed the strengths and difficulties questionnaire (SDQ), the Affect Intensity Measure, and the positive emotions dampening scale. Analysis methods such as descriptive statistics, t-test, Pearson correlations and multiple regression were adapted. The results were as follows: Emotionality and internalizing problem behavior have significant gender differences. Compared to boys, girls have a higher score on negative emotionality and are at a higher risk for internalizing symptoms. However, there are no gender differences on positive emotion dampening. Additionally, in the circumstance that negative emotionality acted as the control variable, positive emotion dampening strategy was (positive) related to internalizing behavior problems. Given the results of this study, it is suggested that coaching deconstructive positive emotion strategies is to assist adolescents with internalizing behavior problems is encouraged.

Keywords: Emotion dampening strategies, internalizing problem behaviors, affect intensity.

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