Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents a fuzzy model for predicting the effects of noise pollution on human work efficiency as a function of noise level, exposure time and age of the operators.
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In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that
Microbial desalination cell (MDC) has been created for expelling water saltiness, power generation, and wastewater administration. The MDC comprised of three chambers (anode, center desalination, and cathode).Were tested ability of type locally isolated bacteria Bacillus spp.in produce electricity to water desalination. In recent study results showed that a remove where the salinity recorded 4000 ppm at room temperature at the voltages of 0.6 volts and less salinity at room temperature at 0.2 volts was 200 ppm. Recent results highlight the need to reduce time for reduce salinity decreased from 3500 ppm to 500 ppm the eleventh day at a voltage of 0.5 volts that depended on type of substrate.
A new method presented in this work to detect the existence of hidden
data as a secret message in images. This method must be applyied only on images which have the same visible properties (similar in perspective) where the human eyes cannot detect the difference between them.
This method is based on Image Quality Metrics (Structural Contents
Metric), which means the comparison between the original images and stego images, and determines the size ofthe hidden data. We applied the method to four different images, we detect by this method the hidden data and find exactly the same size of the hidden data.
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In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
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Honeywords are fake passwords that serve as an accompaniment to the real password, which is called a “sugarword.” The honeyword system is an effective password cracking detection system designed to easily detect password cracking in order to improve the security of hashed passwords. For every user, the password file of the honeyword system will have one real hashed password accompanied by numerous fake hashed passwords. If an intruder steals the password file from the system and successfully cracks the passwords while attempting to log in to users’ accounts, the honeyword system will detect this attempt through the honeychecker. A honeychecker is an auxiliary server that distinguishes the real password from the fake passwords and t
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In this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c
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