Search results for: Analysis of Variance (ANOVA).

Authors: Safak Baykal

Abstract:

The purpose of this study is analyzing the relationship between trust and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: Bonding, homophilous social capital (BoSC), and Bridging, heterophilous social capital (BrSC). These two aspects diverge each other regarding to the social theories. The other concept of the study is Trust (Tr), namely interpersonal trust, willing to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.756 and social capital values (BoSC/BrSC) is not correlated with Tr values of the people.

Keywords: Social capital, interpersonal trust, social network analysis (SNA).

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Authors: Samart Homthong, Wutthipong Moungnoi

Abstract:

Critical success factors (CSFs) and the criteria to measure project success have received much attention over the decades and are among the most widely researched topics in the context of project management. However, although there have been extensive studies on the subject by different researchers, to date, there has been little agreement on the CSFs. The aim of this study is to identify the CSFs that influence the performance of construction projects, and determine their relative importance for different objectives across five stages in the project life cycle. A considerable literature review was conducted that resulted in the identification of 179 individual factors. These factors were then grouped into nine major categories. A questionnaire survey was used to collect data from three groups of respondents: client representatives, consultants, and contractors. Out of 164 questionnaires distributed, 93 were returned, yielding a response rate of 56.7%. Using the mean score, relative importance index, and weighted average method, the top 10 critical factors for each category were identified. The agreement of survey respondents on those categorised factors were analysed using Spearman’s rank correlation. A one-way analysis of variance was then performed to determine whether the mean scores among the various groups of respondents were statistically significant. The findings indicate the most CSFs in each category in procurement phase are: proper procurement programming of materials (time), stability in the price of materials (cost), and determining quality in the construction (quality). They are then followed by safety equipment acquisition and maintenance (health and safety), budgeting allowed in a contractual arrangement for implementing environmental management activities (environment), completeness of drawing documents (productivity), accurate measurement and pricing of bill of quantities (risk management), adequate communication among the project team (human resource), and adequate cost control measures (client satisfaction). An understanding of CSFs would help all interested parties in the construction industry to improve project performance. Furthermore, the results of this study would help construction professionals and practitioners take proactive measures for effective project management.

Keywords: Critical success factors, procurement phase, project life cycle, project performance.

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Authors: Mohammad Mahdi Jabbari, Fardin Boustani

Abstract:

The reservoir of Kowsar dam supply water for different usages such as aquaculture farms , drinking, agricultural and industrial usages for some provinces in south of Iran. The Kowsar dam is located next to the city of Dehdashat in Kohgiluye and Boyerahmad province in southern Iran. There are some towns and villages on the Kowsar dam watersheds, which Dehdasht and Choram are the most important and populated twons in this area, which can to be sources of pollution for water reservoir of the Kowsar dam . This study was done to determine of water pollution of the Kowsar dam reservoir which is one of the most important water resources of Kohkiloye and Boyerahmad and Bushehr provinces in south-west Iran. In this study , water samples during 12 months were collected to examine Biochemical Oxygen Demand (BOD) and Dissolved Oxygen(DO) as a criterion for evaluation of water pollution of the reservoir. In summary ,the study has shown Maximum, average and minimum levels of BOD have observed 25.9 ,9.15 and 2.3 mg/L respectively and statistical parameters of data such as standard deviation , variance and skewness have calculated 7.88, 62 and 1.54 respectively. Finally the results were compared with Iranian national standards. Among the analyzed samples, as the maximum value of BOD (25.9 mg/L) was observed at the May 2010 , was within the maximum admissible limits by the Iranian standards.

Keywords: Kowsar dam, Biochemical Oxygen Demand, water pollution

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Authors: Ghada Salem, Nihal Kabel

Abstract:

Objective: This in vitro study was carried out to assess the microleakage properties of nano-filled glass ionomer in comparison to resin-reinforced glass ionomers. Material and Methods: 40 deciduous molar teeth were included in this study. Class-II cavity was prepared in a standard form for all the specimens. The teeth were randomly distributed into two groups (20 per group) according to the restorative material used either nano-glass ionomer or Photac Fill glass ionomer restoration. All specimens were thermocycled for 1000 cycles between 5 and 55 °C. After that, the teeth were immersed in 2% methylene blue dye then sectioned and evaluated under a stereomicroscope. Microleakage was assessed using linear dye penetration and on a scale from zero to five. Results: Two way ANOVA test revealed a statistically significant lower degree of microleakage in both occlusal and gingival restorations (0.4±0.2), (0.9±0.1) for nano-filled glass ionomer group in comparison to resin modified glass ionomer (2.3±0.7), (2.4±0.5). No statistical difference was found between gingival and occlusal leakage regarding the effect of the measured site. Conclusion: Nano-filled glass ionomer shows superior sealing ability which enables this type of restoration to be used in minimum invasive treatment.

Keywords: Microleakage, nano-ionomer, resin-reinforced glass ionomer, proximal cavity preparation.

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Authors: Seongmin Yim

Abstract:

The Korean government has applied preliminary feasibility study for a new R&D program over about $50 Million since 2008 as a part of official process in budget planning. The investigations of technology, policy, and economics are carried out separately to arrive at a definite result: whether a program is feasible or unfeasible. This paper describes the concept and check-points related to technological analysis from a preliminary evaluation’s stand-point. First of all, the fundamental concept of technological analysis in evaluation systems such as Program Assessment Rating Tool (PART) by Office of Management and Budget (OMB) and Evaluation Methods by Department of Energy (DOE) in the United States, the Green Book in the United Kingdom are reviewed. After the review, customized questionnaire for technological analysis are developed. Conclusively, limitations and further research directions are provided.

Keywords: Preliminary Feasibility Study, R&D Program, Evaluation System, Technological analysis, R&D Logic Analysis.

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Authors: Hooman Hoodat, Hassan Rashidi

Abstract:

Despite various methods that exist in software risk management, software projects have a high rate of failure. When complexity and size of the projects are increased, managing software development becomes more difficult. In these projects the need for more analysis and risk assessment is vital. In this paper, a classification for software risks is specified. Then relations between these risks using risk tree structure are presented. Analysis and assessment of these risks are done using probabilistic calculations. This analysis helps qualitative and quantitative assessment of risk of failure. Moreover it can help software risk management process. This classification and risk tree structure can apply to some software tools.

Keywords: Risk analysis, risk assessment, risk classification, risk tree.

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Authors: Z. Pavlík, J. Kočí, M. Pavlíková, R. Černý

Abstract:

Combined experimental and computational analysis of hygrothermal performance of an interior thermal insulation system applied on a brick wall is presented in the paper. In the experimental part, the functionality of the insulation system is tested at simulated difference climate conditions using a semi-scale device. The measured temperature and relative humidity profiles are used for the calibration of computer code HEMOT that is finally applied for a long-term hygrothermal analysis of the investigated structure.

Keywords: Additional thermal insulation, hygrothermal analysis, semi-scale testing, long-term computational analysis

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Authors: Chompunut Jantarasorn, Chutima Prommak

Abstract:

This paper presents an intensive measurement studying of the network performance analysis when IEEE 802.11g Wireless Local Area Networks (WLAN) coexisting with IEEE 802.15.4 Wireless Personal Area Network (WPAN). The measurement results show that the coexistence between both networks could increase the Frame Error Rate (FER) of the IEEE 802.15.4 networks up to 60% and it could decrease the throughputs of the IEEE 802.11g networks up to 55%.

Keywords: Wireless performance analysis, Coexistence analysis, IEEE 802.11g, IEEE 802.15.4.

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Authors: C. Ardil, A. M. Pashaev, R.A. Sadiqov, P. Abdullayev

Abstract:

In this paper, multiple criteria decision making analysis technique, is presented for ranking and selection of a set of determined alternatives - fighter aircraft - which are associated with a set of decision factors. In fighter aircraft design, conflicting decision criteria, disciplines, and technologies are always involved in the design process. Multiple criteria decision making analysis techniques can be helpful to effectively deal with such situations and make wise design decisions. Multiple criteria decision making analysis theory is a systematic mathematical approach for dealing with problems which contain uncertainties in decision making. The feasibility and contributions of applying the multiple criteria decision making analysis technique in fighter aircraft selection analysis is explored. In this study, an integrated framework incorporating multiple criteria decision making analysis technique in fighter aircraft analysis is established using entropy objective weighting method. An improved integrated multiple criteria decision making analysis method is utilized to aggregate the multiple decision criteria into one composite figure of merit, which serves as an objective function in the decision process. Therefore, it is demonstrated that the suitable multiple criteria decision making analysis method with decision solution provides an effective objective function for the decision making analysis. Considering that the inherent uncertainties and the weighting factors have crucial decision impacts on the fighter aircraft evaluation, seven fighter aircraft models for the multiple design criteria in terms of the weighting factors are constructed. The proposed multiple criteria decision making analysis model is based on integrated entropy index procedure, and additive multiple criteria decision making analysis theory. Hence, the applicability of proposed technique for fighter aircraft selection problem is considered. The constructed multiple criteria decision making analysis model can provide efficient decision analysis approach for uncertainty assessment of the decision problem. Consequently, the fighter aircraft alternatives are ranked based their final evaluation scores, and sensitivity analysis is conducted.

Keywords: Fighter Aircraft, Fighter Aircraft Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, MCDMA

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Authors: Kuo-Cheng Liu

Abstract:

Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.

Keywords: Just-noticeable distortion (JND), discrete cosine transform (DCT), JPEG.

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Authors: Sujit K. Basak

Abstract:

This paper presents a comparison of reference management software between RefWorks and Zotero. The results were drawn by comparing two software and the novelty of this paper is the comparative analysis of software and it has shown that ReftWorks can import more information from the Google Scholar for the researchers. This finding could help to know researchers to use the reference management software.

Keywords: Analysis, comparative analysis, reference management software, researchers.

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Authors: Hui-Chuan Chu, Min-Ju Liao, Wei-Kai Cheng, William Wei-Jen Tsai, Yuh-Min Chen

Abstract:

Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.

Keywords: Emotion classification, Physiological and facial Expression measures, Students with autism, Mathematics e-learning.

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Authors: Hyeong-Geon Lee, Jae-Young Park, Suk-ki Lee, Jong-Tae Kim

Abstract:

The LMS adaptive filter has several parameters which can affect their performance. From among these parameters, most papers handle the step size parameter for controlling the performance. In this paper, we approach three parameters: step-size, filter tap-size and filter form. The regression analysis is used for defining the relation between parameters and performance of LMS adaptive filter with using the system level simulation results. The results present that all parameters have performance trends in each own particular form, which can be estimated from equations drawn by regression analysis.

Keywords: System level model, adaptive LMS FIR filter, regression analysis, systemC.

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Authors: Antoine Karam, Lotfi Khiari, Bruno Breton, Alfred Jaouich

Abstract:

Anthropogenic sources of zinc (Zn), including industrial emissions and effluents, Zn–rich fertilizer materials and pesticides containing Zn, can contribute to increasing the concentration of soluble Zn at levels toxic to plants in acid sandy soils. The application of municipal sewage sludge or biosolids (MBS) which contain metal immobilizing agents on coarse-textured soils could improve the metal sorption capacity of the low-CEC soils. The purpose of this experiment was to evaluate the sorption of Zn in surface samples (0-15 cm) of six Quebec (Canada) soils amended with MBS (pH 6.9) from Val d’Or (Quebec, Canada). Soil samples amended with increasing amounts (0 to 20%) of MBS were equilibrated with various amounts of Zn as ZnCl₂ in 0.01 M CaCl₂ for 48 hours at room temperature. Sorbed Zn was calculated from the difference between the initial and final Zn concentration in solution. Zn sorption data conformed to the linear form of Freundlich equation. The amount of sorbed Zn increased considerably with increasing MBS rate. Analysis of variance revealed a highly significant effect (p ≤ 0.001) of soil texture and MBS rate on the amount of sorbed Zn. The average values of the Zn-sorption capacity of MBS-amended coarse-textured soils were lower than those of MBS-amended fine textured soils. The two sandy soils (86-99% sand) amended with MBS retained 2- to 5-fold Zn than those without MBS (control). Significant Pearson correlation coefficients between the Zn sorption isotherm parameter, i.e. the Freundlich sorption isotherm (K_F), and commonly measured physical and chemical entities were obtained. Among all the soil properties measured, soil pH gave the best significant correlation coefficients (p ≤ 0.001) for soils receiving 0, 5 and 10% MBS. Furthermore, K_F values were positively correlated with soil clay content, exchangeable basic cations (Ca, Mg or K), CEC and clay content to CEC ratio. From these results, it can be concluded that (i) municipal biosolids provide sorption sites that have a strong affinity for Zn, (ii) both soil texture, especially clay content, and soil pH are the main factors controlling anthropogenic Zn sorption in the municipal biosolids-amended soils, and (iii) the effect of municipal biosolids on Zn sorption will be more pronounced for a sandy soil than for a clay soil.

Keywords: Metal, recycling, sewage sludge, trace element.

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Authors: Adel Assiri, Ahmed Emam, Hmood Al-Dossari

Abstract:

Sentiment analysis (SA) has received growing attention in Arabic language research. However, few studies have yet to directly apply SA to Arabic due to lack of a publicly available dataset for this language. This paper partially bridges this gap due to its focus on one of the Arabic dialects which is the Saudi dialect. This paper presents annotated data set of 4700 for Saudi dialect sentiment analysis with (K= 0.807). Our next work is to extend this corpus and creation a large-scale lexicon for Saudi dialect from the corpus.

Keywords: Arabic, Sentiment Analysis, Twitter, annotation.

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Authors: Chvalkovska, J., Jansky, P., Mejstrik, M.

Abstract:

The objective of this article is to discuss the potential of economic analysis as a tool for identification and evaluation of corruption in legislative acts. We propose that corruption be perceived as a risk variable within the legislative process. Therefore we find it appropriate to employ risk analysis methods, used in various fields of economics, for the evaluation of corruption in legislation. Furthermore we propose the incorporation of these methods into the so called corruption impact assessment (CIA), the general framework for detection of corruption in legislative acts. The applications of the risk analysis methods are demonstrated on examples of implementation of proposed CIA in the Czech Republic.

Keywords: corruption; corruption impact assessment (CIA); legislative; legislative process; risk analysis; Czech Republic

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Authors: Raif Parlakkaya, Huseyin Cetin, Duygu Irdiren

Abstract:

By the development of World Wide Web, the usage rate of Internet has rapidly grown globally; and provided a basis for the emergence of electronic business. As well as other sectors, the banking sector has adopted the use of internet with the developments in information and communication technologies. Due to the public disclosure and transparency principle of Corporate Governance, the importance of information disclosure of banks on their web sites has increased significantly. For the purpose of this study, a Bank Disclosure Attribute Index (BDAI) in Turkey has been constructed through classifying the information disclosure on banks’ web sites into general, financial, investors and corporate governance attributes. All 47 banks in Turkish Banking System have been evaluated according to the index with the aim of providing a comparison between banks. By Chi Square Test, Pearson Correlation, T-Test, and ANOVA statistical tools, it has been concluded that the majority of banks in Turkey have shared information on their web sites adequately with respect to their total index score. Although there is a positive correlation between various types of information on banks’ web sites, there is no uniformity among them. Also, no significant difference between various types of information disclosure and bank types has been observed. Compared with the total index score averages of the five largest banks in Turkey, there are some banks that need to improve the content of their web sites.

Keywords: Banking sector, public disclosure, Turkey, web site evaluation.

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Authors: Heroe Wijanto, Sugihartono, Suhartono Tjondronegoro, Kuspriyanto

Abstract:

The use of High Order Statistics (HOS) analysis is expected to provide so many candidates of features that can be selected for pattern recognition. More candidates of the feature can be extracted using simple manipulation through a specific mathematical function prior to the HOS analysis. Feature extraction method using HOS analysis combined with Difference to the Nth-Power manipulation has been examined in application for Automatic Modulation Recognition (AMR) to perform scheme recognition of three digital modulation signal, i.e. QPSK-16QAM-64QAM in the AWGN transmission channel. The simulation results is reported when the analysis of HOS up to order-12 and the manipulation of Difference to the Nth-Power up to N = 4. The obtained accuracy rate of AMR using the method of Simple Decision obtained 90% in SNR > 10 dB in its classifier, while using the method of Voted Decision is 96% in SNR > 2 dB.

Keywords: modulation, automatic modulation recognition, feature analysis, feature manipulation.

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Authors: Jheng-Long Wu, Pei-Chann Chang, Shih-Ling Chang, Liang-Chih Yu, Jui-Feng Yeh, Chin-Sheng Yang

Abstract:

The Major Depressive Disorder has been a burden of medical expense in Taiwan as well as the situation around the world. Major Depressive Disorder can be defined into different categories by previous human activities. According to machine learning, we can classify emotion in correct textual language in advance. It can help medical diagnosis to recognize the variance in Major Depressive Disorder automatically. Association language incremental is the characteristic and relationship that can discovery words in sentence. There is an overlapping-category problem for classification. In this paper, we would like to improve the performance in classification in principle of no overlapping-category problems. We present an approach that to discovery words in sentence and it can find in high frequency in the same time and can-t overlap in each category, called Association Language Features by its Category (ALFC). Experimental results show that ALFC distinguish well in Major Depressive Disorder and have better performance. We also compare the approach with baseline and mutual information that use single words alone or correlation measure.

Keywords: Association language features, Emotion Classification, Overlap-Category Feature, Nature Language Processing.

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Authors: Kyoung-Jae Kim, Hyunchul Ahn

Abstract:

This study proposes novel hybrid social network analysis and collaborative filtering approach to enhance the performance of recommender systems. The proposed model selects subgroups of users in Internet community through social network analysis (SNA), and then performs clustering analysis using the information about subgroups. Finally, it makes recommendations using cluster-indexing CF based on the clustering results. This study tries to use the cores in subgroups as an initial seed for a conventional clustering algorithm. This model chooses five cores which have the highest value of degree centrality from SNA, and then performs clustering analysis by using the cores as initial centroids (cluster centers). Then, the model amplifies the impact of friends in social network in the process of cluster-indexing CF.

Keywords: Social network analysis, Recommender systems, Collaborative filtering, Customer relationship management

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Authors: Sujit K. Basak

Abstract:

This paper presents a comparison of the reference management software between Zotero and Mendeley and the results were drawn by comparing the two software’s. The novelty of this paper is the comparative analysis of the software and it has shown that Mendeley can import more information from the Google Scholar for the researchers. This finding can help to know researchers to use the reference management software.

Keywords: Analysis, comparative analysis, zotero, researchers, Mendeley.

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

Abstract:

Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: Satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization.

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Authors: M.R. Safizadeh, M. Hussein, K. F. Samat, M.S. Che Kob, M.S. Yaacob, M.Z. Md Zain

Abstract:

The aim of this paper is to present the kinematic analysis and mechanism design of an assistive robotic leg for hemiplegic and hemiparetic patients. In this work, the priority is to design and develop the lightweight, effective and single driver mechanism on the basis of experimental hip and knee angles- data for walking speed of 1 km/h. A mechanism of cam-follower with three links is suggested for this purpose. The kinematic analysis is carried out and analysed using commercialized MATLAB software based on the prototype-s links sizes and kinematic relationships. In order to verify the kinematic analysis of the prototype, kinematic analysis data are compared with the experimental data. A good agreement between them proves that the anthropomorphic design of the lower extremity exoskeleton follows the human walking gait.

Keywords: Kinematic analysis, assistive robotic leg, lower extremity exoskeleton, cam-follower mechanism.

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Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

Abstract:

Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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Authors: Ali Al-Ataby , Fawzi Al-Naima

Abstract:

Symbolic Circuit Analysis (SCA) is a technique used to generate the symbolic expression of a network. It has become a well-established technique in circuit analysis and design. The symbolic expression of networks offers excellent way to perform frequency response analysis, sensitivity computation, stability measurements, performance optimization, and fault diagnosis. Many approaches have been proposed in the area of SCA offering different features and capabilities. Numerical Interpolation methods are very common in this context, especially by using the Fast Fourier Transform (FFT). The aim of this paper is to present a method for SCA that depends on the use of Wavelet Transform (WT) as a mathematical tool to generate the symbolic expression for large circuits with minimizing the analysis time by reducing the number of computations.

Keywords: Numerical Interpolation, Sparse Matrices, SymbolicAnalysis, Wavelet Transform.

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Authors: Azam Tabatabaee, Fereshteh Dastgoshadeh, Akram Tabatabaee

Abstract:

This paper describes the use of by-products as adsorbents for removing heavy metals from aqueous effluent solutions. Products of almond skin, walnut shell, saw dust, rice bran and egg shell were evaluated as metal ion adsorbents in aqueous solutions. A comparative study was done with commercial adsorbents like ion exchange resins and activated carbon too. Batch experiments were investigated to determine the affinity of all of biomasses for, Cd(ΙΙ), Cr(ΙΙΙ), Ni(ΙΙ), and Pb(ΙΙ) metal ions at pH 5. The rate of metal ion removal in the synthetic wastewater by the biomass was evaluated by measuring final concentration of synthetic wastewater. At a concentration of metal ion (50 mg/L), egg shell adsorbed high levels (98.6 – 99.7%) of Pb(ΙΙ) and Cr(ΙΙΙ) and walnut shell adsorbed high levels (35.3 – 65.4%) of Ni(ΙΙ) and Cd(ΙΙ). In this study, it has been shown that by-products were excellent adsorbents for removal of toxic ions from wastewater with efficiency comparable to commercially available adsorbents, but at a reduced cost. Also statistical studies using Independent Sample t Test and ANOVA Oneway for statistical comparison between various elements adsorption showed that there isn’t a significant difference in some elements adsorption percentage by by-products and commercial adsorbents.

Keywords: Adsorbents, heavy metals, commercial adsorbents, wastewater, by-products.

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Authors: Alireza Barari

Abstract:

Physical activity and diet are factors that influence the body's structure. The purpose of this study was to compare the effects of four weeks of resistance training, and glutamine supplement consumption on growth hormone (GH), and Insulin-like growth factor 1 (IGF-1) Axis. 40 amateur male bodybuilders, participated in this study. They were randomly divided into four equal groups, Resistance (R), Glutamine (G), Resistance with Glutamine (RG), and Control (C). The R group was assigned to a four week resistance training program, three times/week, three sets of 10 exercises with 6-10 repetitions, at the 80-95% 1RM (One Repetition Maximum), with 120 seconds rest between sets), G group is consuming l-glutamine (0.1 g/kg^-1/day^-1), RG group resistance training with consuming L-glutamine, and C group continued their normal lifestyle without exercise training. GH, IGF1, IGFBP-III plasma levels were measured before and after the protocol. One-way ANOVA indicated significant change in GH, IGF, and IGFBP-III between the four groups, and the Tukey test demonstrated significant increase in GH, IGF1, IGFBP-III plasma levels in R, and RG group. Based upon these findings, we concluded that resistance training at 80-95% 1RM intensity, and resistance training along with oral glutamine shows significantly increase secretion of GH, IGF-1, and IGFBP-III in amateur males, but the addition of oral glutamine to the exercise program did not show significant difference in GH, IGF-1, and IGFBP-III.

Keywords: Strength, glutamine, growth hormone, insulin-like growth factor 1.

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Authors: M. Amir Abas, M. Dahlui

Abstract:

This paper presents the development of analysis tools for Home Agriculture project. The tools are required for monitoring the condition of greenhouse which involves two components: measurement hardware and data analysis engine. Measurement hardware is functioned to measure environment parameters such as temperature, humidity, air quality, dust and etc while analysis tool is used to analyse and interpret the integrated data against the condition of weather, quality of health, irradiance, quality of soil and etc. The current development of the tools is completed for off-line data recorded technique. The data is saved in MMC and transferred via ZigBee to Environment Data Manager (EDM) for data analysis. EDM converts the raw data and plot three combination graphs. It has been applied in monitoring three months data measurement for irradiance, temperature and humidity of the greenhouse..

Keywords: Monitoring, Environment, Greenhouse, Analysis tools

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Authors: S. H. Yahaya, J. M. Ali, M. R. Arham

Abstract:

This paper presents the analysis of duct design using static and dynamic approaches. The static approach is used to find out applicability between the design and material applied. The material used in this paper is Thermoplastic Olefins (TPO). For the dynamic approach, the focusing is only on the CFD simulations. The fatigue life in this design and material applied also covered.

Keywords: CFD, structural analysis, fluid analysis, duct design, fatigue life

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Authors: M. Sitoe, O. Zacarias

Abstract:

University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: Evasion and retention, cross validation, bagging, stacking.

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