The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to minimize the total costs, Where the approved model was able to minimize the total costs by 25%. A future study investigating optimization heuristic with stochastics demand would be very interesting.
Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix
... Show MoreThe present study aimed to identify teaching problems which facing the teachers for first three grades classes, and if these problems different according to some variables teacher qualification, experience period, class grade). The study sample consist of (137 )
female teachers who teach the first three grades in Braimy city in Oman, teachers spread in five government schools. Both researchers developed questionnaire to measure problems faced by the mentioned teachers, consist of 50 questions distributed into 4 dimensions (teacher, students, the curriculum, the evaluations), Also researchers checked questionnaire validity and stability. The results indicate to: The most common probl
... Show MoreIn this paper, first we refom1Ulated the finite element model
(FEM) into a neural network structure using a simple two - dimensional problem. The structure of this neural network is described
, followed by its application to solving the forward and inverse problems. This model is then extended to the general case and the advantages and di sadvantages of this approach are descri bed along with an analysis of the sensi tivity of
... Show MoreAbstract
Prescribing drugs to patients to treat ailments or reducing their morbidity may not be enough, even if the drugs were all indicated and in the right dose. Clinical pharmacists play a pivotal role in conducting information and instruction to patients and conveying feedback to treating physician when appropriate, and the final goal is in the interest of the patient. Identification and classification of drug related problems and discussing them with the health care providers. Prospective, interventional, clinical study for 180 hemodialysis patients, and was designed as two phases, an observational phase to identify drug related problems and classifying them according to the latest Pharmaceutical
... Show MoreScheduling problems have been treated as single criterion problems until recently. Many of these problems are computationally hard to solve three as single criterion problems. However, there is a need to consider multiple criteria in a real life scheduling problem in general. In this paper, we study the problem of scheduling jobs on a single machine to minimize total tardiness subject to maximum earliness or tardiness for each job. And we give algorithm (ETST) to solve the first problem (p1) and algorithm (TEST) to solve the second problem (p2) to find an efficient solution.
The tremendous political transformations that took place in Iraq after 2003 led by the USA and its allies led to a change of its political system under the slogan of liberating Iraq from dictatorship, establishing a democratic system and spreading freedom among members of the society.
However, democracy was a mantle under which the US intended to achieve its expansionist ambitions in the region. It did not come to liberate Iraq as it claimed, but it occupied Iraq and all its materialistic and human resources. Thus, this change resulted in lots of negative events and societal pests that affected the entire social system and values. Youth is an important segment; it is one of the most affected age groups with the happenings and accident
The aims of the paper are to present a modified symmetric fuzzy approach to find the best workable compromise solution for quadratic fractional programming problems (QFPP) with fuzzy crisp in both the objective functions and the constraints. We introduced a modified symmetric fuzzy by proposing a procedure, that starts first by converting the quadratic fractional programming problems that exist in the objective functions to crisp numbers and then converts the linear function that exists in the constraints to crisp numbers. After that, we applied the fuzzy approach to determine the optimal solution for our quadratic fractional programming problem which is supported theoretically and practically. The computer application for the algo
... Show MoreElectrocoagulation process was employed for the treatment of river water flows in Iraq. In this study, a batch Electrocoagulation process was used to treat river water taken from Al - Qadisiyah water treatment plant. electrolysis time, voltage and inter-electrode spacing were the most important parameters to study . A statistical model was developed using the RSM model. The optimum condition after studying the parameter effect the process was 1 cm separating, 30 volts . The RSM model shows the ideal condition of removal for both the TSS and turbidity at 1 cm, 20 volts and 55 min.
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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