Fuzzy Population-Based Meta-Heuristic Approaches for Attribute Reduction in Rough Set Theory

One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm, to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Prediction of Compressive Strength of Concrete from Early Age Test Result Using Design of Experiments (RSM)

Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates ‘finding the flats’ on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarseaggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.

A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

The Dilemma of Retention in the Context of Rapidly Growing Economies Based on the Effectiveness of HRM Policies: A Case Study of Qatar

In 2009, the new HRM policy was implemented in Qatar for public sector organisations. The purpose of this research is to examine how Qatar’s 2009 HRM policy was significant in influencing employee retention in public organisations. The conducted study utilised quantitative methodology to analyse the data on employees’ perceptions of such HRM practices as Performance Management, Rewards and Promotion, Training and Development associated with the HRM policy in public organisations in comparison to semi-private organisations. Employees of seven public and semi-private organisations filled in the questionnaire based on the 5-point Likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Performance Management had the relationship with Employee Retention, and Rewards and Promotion influenced Job Satisfaction in public organisations. Relationship between Job Satisfaction and Employee Retention was also observed. However, no significant differences were observed in the role of HRM practices in public and semi-private organisations.

Shear Capacity of Rectangular Duct Panel Experiencing Internal Pressure

The end panels of a large rectangular industrial duct, which experience significant internal pressures, also experience considerable transverse shear due to transfer of gravity loads to the supports. The current design practice of such thin plate panels for shear load is based on methods used for the design of plate girder webs. The structural arrangements, the loadings and the resulting behavior associated with the industrial duct end panels are, however, significantly different from those of the web of a plate girder. The large aspect ratio of the end panels gives rise to multiple bands of tension fields, whereas the plate girder web design is based on one tension field. In addition to shear, the industrial end panels are subjected to internal pressure which in turn produces significant membrane action. This paper reports a study which was undertaken to review the current industrial analysis and design methods and to propose a comprehensive method of designing industrial duct end panels for shear resistance. In this investigation, a nonlinear finite element model was developed to simulate the behavior of industrial duct end panel, along with the associated edge stiffeners, subjected to transverse shear and internal pressures. The model considered the geometric imperfections and constitutive relations for steels. Six scale independent dimensionless parameters that govern the behavior of such end panel were identified and were then used in a parametric study. It was concluded that the plate slenderness dominates the shear strength of stockier end panels, and whereas, both the plate slenderness and the aspect ratio influence the shear strength of slender end panels. Based on these studies, this paper proposes design aids for estimating the shear strength of rectangular duct end panels.

Spatial Structure of First-Order Voronoi for the Future of Roundabout Cairo since 1867

The Haussmannization plan of Cairo in 1867 formed a regular network of roundabout spaces, though deteriorated at present. The method of identifying the spatial structure of roundabout Cairo for conservation matches the voronoi diagram with the space syntax through their geometrical property of spatial convexity. In this initiative, the primary convex hull of first-order voronoi adopts the integral and control measurements of space syntax on Cairo’s roundabout generators. The functional essence of royal palaces optimizes the roundabout structure in terms of spatial measurements and the symbolic voronoi projection of 'Tahrir Roundabout' over the Giza Nile and Pyramids. Some roundabouts of major public and commercial landmarks surround the pole of 'Ezbekia Garden' with a higher control than integral measurements, which filter the new spatial structure from the adjacent traditional town. Nevertheless, the least integral and control measures correspond to the voronoi contents of pollutant workshops and the plateau of old Cairo Citadel with the visual compensation of new royal landmarks on top. Meanwhile, the extended suburbs of infinite voronoi polygons arrange high control generators of chateaux housing in 'garden city' environs. The point pattern of roundabouts determines the geometrical characteristics of voronoi polygons. The measured lengths of voronoi edges alternate between the zoned short range at the new poles of Cairo and the distributed structure of longer range. Nevertheless, the shortest range of generator-vertex geometry concentrates at 'Ezbekia Garden' where the crossways of vast Cairo intersect, which maximizes the variety of choice at different spatial resolutions. However, the symbolic 'Hippodrome' which is the largest public landmark forms exclusive geometrical measurements, while structuring a most integrative roundabout to parallel the royal syntax. Overview of the symbolic convex hull of voronoi with space syntax interconnects Parisian Cairo with the spatial chronology of scattered monuments to conceive one universal Cairo structure. Accordingly, the approached methodology of 'voronoi-syntax' prospects the future conservation of roundabout Cairo at the inferred city-level concept.

Competitiveness and Value Creation of Tourism Sector: In the Case of 10 ASEAN Economies

The ASEAN Economic Community (AEC) is the goal of regional economic integration by 2015. In the region, tourism is an activity that is important, especially as a source of foreign currency, a source of employment creation and a source of income bringing to the region. Given the complexity of the issues entailing the concept of sustainable tourism, this paper tries to assess tourism sustainability with the ASEAN, based on a number of quantitative indicators for all the ten economies, Thailand, Myanmar, Laos, Vietnam, Malaysia, Singapore, Indonesia, Philippines, Cambodia, and Brunei. The methodological framework will provide a number of benchmarks of tourism activities in these countries. They include identification of the dimensions; for example, economic, socio-ecologic, infrastructure and indicators, method of scaling, chart representation and evaluation on Asian countries. This specification shows that a similar level of tourism activity might introduce different implementation in the tourism activity and might have different consequences for the socioecological environment and sustainability. The heterogeneity of developing countries exposed briefly here would be useful to detect and prepare for coping with the main problems of each country in their tourism activities, as well as competitiveness and value creation of tourism for ASEAN economic community, and will compare with other parts of the world.

The Effect of Biochar, Inoculated Biochar and Compost Biological Component of the Soil

Biochar can be produced from the waste matter and its application has been associated with returning of carbon in large amounts into the soil. The impacts of this material on physical and chemical properties of soil have been described. The biggest part of the research work is dedicated to the hypothesis of this material’s toxic effects on the soil life regarding its effect on the soil biological component. At present, it has been worked on methods which could eliminate these undesirable properties of biochar. One of the possibilities is to mix biochar with organic material, such as compost, or focusing on the natural processes acceleration in the soil. In the experiment has been used as the addition of compost as well as the elimination of toxic substances by promoting microbial activity in aerated water environment. Biochar was aerated for 7 days in a container with a volume of 20 l. This way modified biochar had six times higher biomass production and reduce mineral nitrogen leaching. Better results have been achieved by mixing biochar with compost.

Job Satisfaction and Motivation as Predictors of Lecturers’ Effectiveness in Nigeria Police Academy

Job satisfaction and motivation have been given an important attention in psychology because they are seen as main instruments in maintaining organizational growth and development; they are also used to accomplish organizational aims and objectives. However, it has been observed that some institutions failed in motivating and stimulating their workers; in contrast, workers may be motivated but not satisfied with the job and failed to perform efficiently and effectively. It is hoped that the study of this nature would be of significance value to all stakeholders in education specifically, lecturers in higher institutions in Nigeria. Also, it is hoped that the findings of this study will enhance lecturers’ effectiveness and performance in discharging their duties. In the light of the above statements, this study investigated whether job satisfaction and motivation predict lecturers’ effectiveness in Nigeria Police Academy, Wudil, Kano State. Correlational research method was adopted for the study, while purposive sampling technique was used to choose the institution and the sampled lectures (70). Simple random sampling technique was used to select one hundred cadets across the academy. Two instruments were used to elicit information from both lecturers and cadets. These were job satisfaction and motivation; and lecturers’ effectiveness Questionnaires. The instruments were subjected to pilot testing and found to have reliability coefficient of 0.69 and 0.71 respectively. The results of the study revealed that there was a significance relationship among job satisfaction, motivation and lecturers effectiveness in Nigeria Police Academy. There was a significance relationship between job satisfaction and lecturers’ effectiveness in Nigeria Police Academy the cal r is 0.21 while the crt r is 0.19. at p

One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data

We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Segmentation of Korean Words on Korean Road Signs

This paper introduces an effective method of segmenting Korean text (place names in Korean) from a Korean road sign image. A Korean advanced directional road sign is composed of several types of visual information such as arrows, place names in Korean and English, and route numbers. Automatic classification of the visual information and extraction of Korean place names from the road sign images make it possible to avoid a lot of manual inputs to a database system for management of road signs nationwide. We propose a series of problem-specific heuristics that correctly segments Korean place names, which is the most crucial information, from the other information by leaving out non-text information effectively. The experimental results with a dataset of 368 road sign images show 96% of the detection rate per Korean place name and 84% per road sign image.

Ethical Perspectives on Implementation of Computer Aided Design Curriculum in Architecture in Nigeria: A Case Study of Chukwuemeka Odumegwu Ojukwu University, Uli

The use of Computer Aided Design (CAD) technologies has become pervasive in the Architecture, Engineering and Construction (AEC) industry. This has led to its inclusion as an important part of the training module in the curriculum for Architecture Schools in Nigeria. This paper examines the ethical questions that arise in the implementation of Computer Aided Design (CAD) Content of the curriculum for Architectural education. Using existing literature, it begins this scrutiny from the propriety of inclusion of CAD into the education of the architect and the obligations of the different stakeholders in the implementation process. It also examines the questions raised by the negative use of computing technologies as well as perceived negative influence of the use of CAD on design creativity. Survey methodology was employed to gather data from the Department of Architecture, Chukwuemeka Odumegwu Ojukwu University Uli, which has been used as a case study on how the issues raised are being addressed. The paper draws conclusions on what will make for successful ethical implementation.

Password Cracking on Graphics Processing Unit Based Systems

Password authentication is one of the widely used methods to achieve authentication for legal users of computers and defense against attackers. There are many different ways to authenticate users of a system and there are many password cracking methods also developed. This paper proposes how best password cracking can be performed on a CPU-GPGPU based system. The main objective of this work is to project how quickly a password can be cracked with some knowledge about the computer security and password cracking if sufficient security is not incorporated to the system.

Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena

A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/ deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

The Effect of Saccharomyces cerevisiae Live Yeast Culture on Microbial Nitrogen Supply to Small Intestine in Male Kivircik Yearlings Fed with Different Forage-Concentrate Ratios

The aim of the study was to investigate the effect of Saccharomyces cerevisiae (SC) live yeast culture on microbial protein supply to small intestine in Kivircik male yearlings when fed with different ratio of forage and concentrate diets. Four Kivircik male yearlings with permanent rumen canula were used in the experiment. The treatments were allocated to a 4x4 Latin square design. Diet I consisted of 70% alfalfa hay and 30% concentrate, Diet II consisted of 30% alfalfa hay and 70% concentrate, Diet I and II were supplemented with a SC. Daily urine was collected and stored at -20°C until analysis. Calorimetric methods were used for the determination of urinary allantoin and creatinine levels. The estimated microbial N supply to small intestine for Diets I, I+SC, II and II+SC were 2.51, 2.64, 2.95 and 3.43 g N/d respectively. Supplementation of Diets I and II with SC significantly affected the allantoin levels in μmol/W0.75 (p

Vapor Phase Transesterification of Dimethyl Malonate with Phenol over Cordierite Honeycomb Coated with Zirconia and Its Modified Forms

The transesterification of dimethyl malonate (DMM) with phenol has been studied in vapour phase over cordierite honeycomb coated with solid acid catalysts such as ZrO2, Mo(VI)/ZrO2 and SO42-/ZrO2. The catalytic materials were prepared honeycomb coated, powder forms, and characterized for their total surface acidity by NH3-TPD and crystalinity by powder XRD methods. Phenyl methyl malonate (PMM) and diphenyl malonate (DPM) were obtained as the reaction products. A good conversion of DMM (up to 82%) of MPM with 95% selectivity was observed when the reactions were carried out at a catalyst bed temperature of 200 °C and flow-rate of 10 mL/h in presence of Mo(VI)/ZrO2 as catalyst. However, over SO4^2-/ZrO2 catalyst, the yield of DPM was found to be higher. The results have been interpreted based on the variation of acidic properties and powder XRD phases of zirconia on incorporation of Mo(VI) or SO42– ions. Transesterification reactions were also carried out over powder forms of the catalytic materials and the yield of the desired phenyl ester products were compared with that of the HC coated catalytic materials. The solid acids were found to be reusable when used for at least 5 reaction cycles.

Dynamic Fault Diagnosis for Semi-Batch Reactor under Closed-Loop Control via Independent Radial Basis Function Neural Network

In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. Several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature, and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

A Bi-Objective Model to Address Simultaneous Formulation of Project Scheduling and Material Ordering

Concurrent planning of project scheduling and material ordering has been increasingly addressed within last decades as an approach to improve the project execution costs. Therefore, we have taken the problem into consideration in this paper, aiming to maximize schedules quality robustness, in addition to minimize the relevant costs. In this regard, a bi-objective mathematical model is developed to formulate the problem. Moreover, it is possible to utilize the all-unit discount for materials purchasing. The problem is then solved by the E-constraint method, and the Pareto front is obtained for a variety of robustness values. The applicability and efficiency of the proposed model is tested by different numerical instances, finally.

The Effects of Soil Chemical Characteristics on Accumulation of Native Selenium by Zea mays Grains in Maize Belt in Kenya

Selenium is an-antioxidant which is important for human health enters food chain through crops. In Kenya Zea mays is consumed by 96% of population hence is a cheap and convenient method to provide selenium to large number of population. Several soil factors are known to have antagonistic effects on selenium speciation hence the uptake by Zea mays. There are no studies in Kenya that has been done to determine the effects of soil characteristics (pH, Tcarbon, CEC, Eh) affect accumulation of selenium in Zea mays grains in Maize Belt in Kenya. About 100 Zea mays grain samples together with 100 soil samples were collected from the study site put in separate labeled Ziplocs and were transported to laboratories at room temperature for analysis. Maize grains were analyzed for selenium while soil samples were analyzed for pH, Cat Ion Exchange Capacity, total carbon, and electrical conductivity. The mean selenium in Zea mays grains varied from 1.82 ± 0.76 mg/Kg to 11±0.86 mg/Kg. There was no significant difference between selenium levels between different grain batches {χ (Df =76) = 26.04 P= 1.00} The pH levels varied from 5.43± 0.58 to 5.85± 0.32. No significant correlations between selenium in grains and soil pH (Pearson’s correlations = - 0.143), and between selenium levels in grains and the four (pH, Tcarbon, CEC, Eh) soil chemical characteristics {F (4,91) = 0.721 p = 0.579} was observed. It can be concluded that the soil chemical characteristics in the study site did not significantly affect the accumulation of native selenium in Zea mays grains.