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Solid Waste Treatment Using Multi-Criteria Decision Support Methods Case Study Lattakia City
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Lattakia city faces many problems related to the mismanagement of solid waste, as the disposal process is limited to the random Al-Bassa landfill without treatment. Therefore, solid waste management poses a special challenge to decision-makers by choosing the appropriate tool that supports strategic decisions in choosing municipal solid waste treatment methods and evaluating their management systems. As the human is primarily responsible for the formation of waste, this study aims to measure the degree of environmental awareness in the Lattakia Governorate from the point of view of the research sample members and to discuss the effect of the studied variables (place of residence, educational level, gender, age, and professional status) on the level of environmental awareness. Data were collected and analyzed using the SPSS.21 statistical package. This study also presents a methodology to find the optimal scenario for solid waste treatment using the hierarchical analysis method represented by Expert Choice 11.1.

The study found that there is an environmental awareness about the danger of the increasing percentage of environmental pollution and the presence of a social willingness to contribute to solid waste management, such as household sorting and working in voluntary associations. Environmental awareness is spreading throughout the province, but more attention is paid to the environment in the countryside than in the city. It was also found that environmental awareness is linked to the cultural level, and it was equal between males and females.

The study also provided the optimal treatment method for solid waste according to the theory of hierarchical analysis, where the biogas production method ranked first with a rate of 35.5%, followed by the composting production method with 22.6%, the recycling method with 17.4%, followed by the incineration method by 15%. The sanitary landfill method ranked last, with 9.5%.

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Interior Visual Intruders Detection Module Based on Multi-Connect Architecture MCA Associative Memory
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Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role innovative leadership in administrative empowerment (Study analysis of the views of a sample of decision makers in the General Company for Food Industries(
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 Abstract

The objective of the research is to identify the role of innovative leadership in achieving the dimensions of administrative empowerment in the company for the public of food industries. The various variables have shown the importance of innovative leadership to achieve the dimensions of administrative empowerment in both international and local companies. Administrative Empowerment "In order to answer this question, a virtual model was developed to reflect the relationship and impact between innovative leadership and administrative empowerment. The research was based on the analytical descriptive approach.  the research community, The company represented the general company for food industries, retrie

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Multi-Dimensional Angle of Arrival Estimation by Circular Phased Adaptive Array Antennas
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In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The Role of SMEs in Economic Development in Jordan: The Case of Al Hassan Industrial Estate
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This study aimed at highlighting the role of small and medium enterprises in bringing about economic development in Jordan. The study examined the impact of the number, size of investment and the number of jobs provided by these enterprises on the rate of growth in gross domestic product (GDP) as an indicator for economic development. To achieve its objectives, the study adopted descriptive and quantitative analysis. A linear multi regression model was developed with a growth rate of GDP as dependent variable and the number of institutions, size of investment, and the number of job opportunities as independent variables. The study concluded that each increase by one small or medium enterprise lead to an increase in the rate of gr

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
The objective Effect of Internal and External Environment and its Psychological & Practical Reflection on the Political Decision-Making Process
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The objective Effect of Internal and External Environment and its Psychological & Practical Reflection on the Political Decision-Making Process

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Publication Date
Fri Apr 26 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Solving Tri-criteria: Total Completion Time, Total Earliness, and Maximum Tardiness Using Exact and Heuristic Methods on Single-Machine Scheduling Problems
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Astronomi cal Color Image Compression Using Multilevel Block Truncation Coding –Modified Vector Quantization Technique
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A common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

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