Search results for: Survey data collection

Authors: Walid MOUDANI

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.

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Authors: A.F. Salarashayeri, M. Siosemarde

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Hydraulic conductivity is one parameter important for predicting the movement of water and contaminants dissolved in the water through the soil. The hydraulic conductivity is measured on soil samples in the lab and sometimes tests carried out in the field. The hydraulic conductivity has been related to soil particle diameter by a number of investigators. In this study, 25 set of soil samples with sand texture. The results show approximately success in predicting hydraulic conductivity from particle diameters data. The following relationship obtained from multiple linear regressions on data (R2 = 0.52): Where d10, d50 and d60, are the soil particle diameter (mm) that 10%, 50% and 60% of all soil particles are finer (smaller) by weight and Ks, saturated hydraulic conductivity is expressed in m/day. The results of regression analysis showed that d10 play a more significant role with respect to Ks, saturated hydraulic conductivity (m/day), and has been named as the effective parameter in Ks calculation.

Keywords: hydraulic conductivity, particle diameter, particle-size distribution and soil

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Authors: Daniel M. Muntean, Viorel Ungureanu

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More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Keywords: Adaptive building, energy efficiency, retrofitting, residential buildings, smart grid.

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Authors: Chayaporn Kaensar

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Recently, Job Recommender Systems have gained much attention in industries since they solve the problem of information overload on the recruiting website. Therefore, we proposed Extended Personalized Job System that has the capability of providing the appropriate jobs for job seeker and recommending some suitable information for them using Data Mining Techniques and Dynamic User Profile. On the other hands, company can also interact to the system for publishing and updating job information. This system have emerged and supported various platforms such as web application and android mobile application. In this paper, User profiles, Implicit User Action, User Feedback, and Clustering Techniques in WEKA libraries were applied and implemented. In additions, open source tools like Yii Web Application Framework, Bootstrap Front End Framework and Android Mobile Technology were also applied.

Keywords: Recommendation, user profile, data mining, web technology, mobile technology.

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Authors: Lai Lai Win Kyi, Nay Min Tun

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Sorting appears the most attention among all computational tasks over the past years because sorted data is at the heart of many computations. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. Many parallel sorting algorithms have been investigated for a variety of parallel computer architectures. In this paper, three parallel sorting algorithms have been implemented and compared in terms of their overall execution time. The algorithms implemented are the odd-even transposition sort, parallel merge sort and parallel rank sort. Cluster of Workstations or Windows Compute Cluster has been used to compare the algorithms implemented. The C# programming language is used to develop the sorting algorithms. The MPI (Message Passing Interface) library has been selected to establish the communication and synchronization between processors. The time complexity for each parallel sorting algorithm will also be mentioned and analyzed.

Keywords: Cluster of Workstations, Parallel sorting algorithms, performance analysis, parallel computing and MPI.

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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: A. O. Oladele

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The purpose of this study was to find out the effectiveness of neurological impress method and repeated reading technique on reading fluency of children with learning disabilities. Thirty primary four pupils in three public primary schools participated in the study. There were two experimental groups and a control. This research employed a 3 by 2 factorial matrix and the participants were taught for one session. Two hypotheses were formulated to guide the research. T-test was used to analyse the data gathered, and data analysis revealed that pupils exposed to the two treatment strategies had improvement in their reading fluency. It was recommended that the two strategies used in the study can be used to intervene in reading fluency problems in children with learning disabilities.

Keywords: Learning disabilities, neurological impress method, repeated reading, reading fluency.

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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: 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: Mohammed Erritali

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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: Yang Meng, James L. Patnao

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With the rapid development of information technology and the impact of the epidemic environment, the traditional teaching model can no longer meet the requirements of the development of the times. The development of teaching mechanisms is the inevitable trend of the future development of higher education. We must further promote the informatization of higher education in teaching practice, let modern information technology penetrate and practice in classroom teaching, and provide promising opportunities for the high-quality development of higher education. This article, mainly through the distribution of questionnaires to teachers of colleges and universities, aims to understand the degree of informatization in the teaching of colleges and universities. And on the basis of domestic and foreign scholars' research on higher education informatization, it analyzes the existing problems, and finds the optimal solution based on the needs of education and teaching development. According to the survey results, most college teachers will use information technology in teaching practice, but the information technology teaching tools used by teachers are relatively simple, and most of them use only slides. In addition, backward informatization infrastructure and less informatization training are the main challenges facing the current teaching informatization construction. If colleges and universities can make good use of information technology and multimedia technology and combine it with traditional teaching, it will definitely promote the development of college education and further promote the modernization and informatization of higher education.

Keywords: Higher education, teaching practice, informatization construction, e-education.

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Authors: Taweepol Suesut, Arjin Numsomran, Vittaya Tipsuwanporn

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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: Charbel Geryes Aoun, Loic Lagadec

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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: 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: Vasanta Duggirala, Y. Viswanatha Naidu

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This paper makes a contribution to the on-going debate on conceptualization and lexicalization of cutting and breaking (C&B) verbs by discussing data from Telugu, a language of India belonging to the Dravidian family. Five Telugu native speakers- verbalizations of agentive actions depicted in 43 short video-clips were analyzed. It was noted that verbalization of C&B events in Telugu requires formal units such as simple lexical verbs, explicator compound verbs, and other complex verb forms. The properties of the objects involved, the kind of instruments used, and the manner of action had differential influence on the lexicalization patterns. Further, it was noted that all the complex verb forms encode 'result' and 'cause' sub-events in that order. Due to the polysemy associated with some of the verb forms, our data does not support the straightforward bipartition of this semantic domain.

Keywords: Cluster analysis, Cutting and breaking events, Polysemy, Semantic extension, Telugu.

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Authors: K. Anitha Sheela, J. Tarun Kumar

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HSDPA is a new feature which is introduced in Release-5 specifications of the 3GPP WCDMA/UTRA standard to realize higher speed data rate together with lower round-trip times. Moreover, the HSDPA concept offers outstanding improvement of packet throughput and also significantly reduces the packet call transfer delay as compared to Release -99 DSCH. Till now the HSDPA system uses turbo coding which is the best coding technique to achieve the Shannon limit. However, the main drawbacks of turbo coding are high decoding complexity and high latency which makes it unsuitable for some applications like satellite communications, since the transmission distance itself introduces latency due to limited speed of light. Hence in this paper it is proposed to use LDPC coding in place of Turbo coding for HSDPA system which decreases the latency and decoding complexity. But LDPC coding increases the Encoding complexity. Though the complexity of transmitter increases at NodeB, the End user is at an advantage in terms of receiver complexity and Bit- error rate. In this paper LDPC Encoder is implemented using “sparse parity check matrix" H to generate a codeword at Encoder and “Belief Propagation algorithm "for LDPC decoding .Simulation results shows that in LDPC coding the BER suddenly drops as the number of iterations increase with a small increase in Eb/No. Which is not possible in Turbo coding. Also same BER was achieved using less number of iterations and hence the latency and receiver complexity has decreased for LDPC coding. HSDPA increases the downlink data rate within a cell to a theoretical maximum of 14Mbps, with 2Mbps on the uplink. The changes that HSDPA enables includes better quality, more reliable and more robust data services. In other words, while realistic data rates are only a few Mbps, the actual quality and number of users achieved will improve significantly.

Keywords: AMC, HSDPA, LDPC, WCDMA, 3GPP.

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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

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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: Puvanasvaran, A. P., Suresh V., N. Norazlin

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The Lean Environmental Management Integration System (LEMIS) framework development is integration between lean core element and ISO 14001. The curiosity on the relationship between continuous improvement and sustainability of lean implementation has influenced this study toward LEMIS. Characteristic of ISO 14001 standard clauses and core elements of lean principles are explored from past studies and literature reviews. Survey was carried out on ISO 14001 certified companies to examine continual improvement by implementing the ISO 14001 standard. The study found that there is a significant and positive relationship between Lean Principles: value, value stream, flow, pull and perfection with the ISO 14001 requirements. LEMIS is significant to support the continuous improvement and sustainability. The integration system can be implemented to any manufacturing company. It gives awareness on the importance on why organizations need to sustain its environmental management system. In the meantime, the lean principle can be adapted in order to streamline daily activities of the company. Throughout the study, it had proven that there is no sacrifice or trade-off between lean principles with ISO 14001 requirements. The framework developed in the study can be further simplified in the future, especially the method of crossing each sub requirements of ISO 14001 standard with the core elements of Lean principles in this study.

Keywords: LEMIS, ISO 14001, integration, framework.

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Authors: Hazem M. El-Bakry, Qiangfu Zhao

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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: 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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Authors: Sarah K. Taylor, Miratun M. Saharuddin, Zabri A. Talib

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Cybercrime is on the rise, and yet many Law Enforcement Agencies (LEAs) in Malaysia have no Digital Forensics Laboratory (DFL) to assist them in the attrition and analysis of digital evidence. From the estimated number of 30 LEAs in Malaysia, sadly, only eight of them owned a DFL. All of the DFLs are concentrated in the capital of Malaysia and none at the state level. LEAs are still depending on the national DFL (CyberSecurity Malaysia) even for simple and straightforward cases. A survey was conducted among LEAs in Malaysia owning a DFL to understand their history of establishing the DFL, the challenges that they faced and the significance of the DFL to their case investigation. The results showed that the while some LEAs faced no challenge in establishing a DFL, some of them took seven to 10 years to do so. The reason was due to the difficulty in convincing their management because of the high costs involved. The results also revealed that with the establishment of a DFL, LEAs were better able to get faster forensic result and to meet agency’s timeline expectation. It is also found that LEAs were also able to get more meaningful forensic results on cases that require niche expertise, compared to sending off cases to the national DFL. Other than that, cases are getting more complex, and hence, a continuous stream of budget for equipment and training is inevitable. The result derived from the study is hoped to be used by other LEAs in justifying to their management the benefits of establishing an in-house DFL.

Keywords: Digital forensics, digital forensics laboratory, digital evidence, law enforcement agency.

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Authors: Duong Vannak, Mohd Shahir Liew, Guo Zheng Yew

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Data of wave height and wind speed were collected from three existing oil fields in South China Sea – offshore Peninsular Malaysia, Sarawak and Sabah regions. Extreme values and other significant data were employed for analysis. The data were recorded from 1999 until 2008. The results show that offshore structures are susceptible to unacceptable motions initiated by wind and waves with worst structural impacts caused by extreme wave heights. To protect offshore structures from damage, there is a need to quantify descriptive statistics and determine spectra envelope of wind speed and wave height, and to ascertain the frequency content of each spectrum for offshore structures in the South China Sea shallow waters using measured time series. The results indicate that the process is nonstationary; it is converted to stationary process by first differencing the time series. For descriptive statistical analysis, both wind speed and wave height have significant influence on the offshore structure during the northeast monsoon with high mean wind speed of 13.5195 knots (
= 6.3566 knots) and the high mean wave height of 2.3597 m (
= 0.8690 m). Through observation of the spectra, there is no clear dominant peak and the peaks fluctuate randomly. Each wind speed spectrum and wave height spectrum has its individual identifiable pattern. The wind speed spectrum tends to grow gradually at the lower frequency range and increasing till it doubles at the higher frequency range with the mean peak frequency range of 0.4104 Hz to 0.4721 Hz, while the wave height tends to grow drastically at the low frequency range, which then fluctuates and decreases slightly at the high frequency range with the mean peak frequency range of 0.2911 Hz to 0.3425 Hz.

Keywords: Metocean, Offshore Engineering, Time Series, Descriptive Statistics, Autospectral Density Function, Wind, Wave.

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Authors: Daniel E. Gberevbie, Adewale O. Osibanjo, Anthonia A. Adeniji, Olumuyiwa A. Oludayo

Abstract:

Research has shown that a recruitment policy devoid of gender discrimination enhances employee performance in an organization. Previous studies in Nigeria show that gender discrimination against men and women based on their ethnic, religious and geographical identity is common. This survey, however, focuses on discrimination against women on the basis of gender and performance in government universities in Lagos State, Nigeria. The model used for this study was developed and tested in which one hundred and eighty seven copies of the questionnaire that were administered to respondents as completed by the academic staff of government universities in Lagos State were retrieved. Pearson correlation and regression were utilized for the analysis of the study, and the result showed that managerial roles based on gender discrimination against women in government universities in Lagos State have affected employee job performance negatively. The study concludes that for as long as gender discrimination rather than merit remains the basis for staff employment into positions of authority in Nigerian Universities, enhanced performance is more likely to elude employees and the educational sector in general. 

Keywords: Academic staff, Employee performance, Gender discrimination, Nigeria, Universities.

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Authors: Nahid Ghasemi, Mohammad Goodarzi, Morteza Khosravi

Abstract:

Simultaneous determination of multicomponents of phenol, resorcinol and catechol with a chemometric technique a PCranking artificial neural network (PCranking-ANN) algorithm is reported in this study. Based on the data correlation coefficient method, 3 representative PCs are selected from the scores of original UV spectral data (35 PCs) as the original input patterns for ANN to build a neural network model. The results obtained by iterating 8000 .The RMSEP for phenol, resorcinol and catechol with PCranking- ANN were 0.6680, 0.0766 and 0.1033, respectively. Calibration matrices were 0.50-21.0, 0.50-15.1 and 0.50-20.0 μg ml-1 for phenol, resorcinol and catechol, respectively. The proposed method was successfully applied for the determination of phenol, resorcinol and catechol in synthetic and water samples.

Keywords: Phenol, Resorcinol, Catechol, Principal componentrankingArtificial Neural Network, Chemometrics.

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Authors: Liming Zhang

Abstract:

This paper introduces a new instantaneous frequency computation approach
-Counting Instantaneous Frequency for a general class of signals called simple waves. The classsimple wave contains a wide range of continuous signals for which the concept instantaneous frequency has a perfect physical sense. The concept of
-Counting Instantaneous Frequency also applies to all the discrete data. For all the simple wave signals and the discrete data,
-Counting instantaneous frequency can be computed directly without signal decomposition process. The intrinsic mode functions obtained through empirical mode decomposition belongs to simple wave. So
-Counting instantaneous frequency can be used together with empirical mode decomposition.

Keywords: Instantaneous frequency, empirical mode decomposition, intrinsic mode function.

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

Abstract:

Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. For example rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: Rubber bumper, data acquisition, finite element analysis, support vector regression.

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Authors: Dariush Jafari, Seyed Ali Jafari

Abstract:

The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water.

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

Abstract:

An Acoustic Micro-Energy Harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using Lumped Element Modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Then, AMEH undergoes bandwidth tuning for performance optimization. The AMEH successfully produces 0.9V/(m/s^2) and 1.79μW/(m^2/s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: Piezoelectric, acoustic, energy harvester, thermoacoustic.

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