In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication cost. Unlike MSL* which chooses all normal nodes found in the neighbor, the proposed scheme uses set theory to only select intersected nodes. To evaluate our method, we simulate in our proposed scheme the use of the same MSL* settings and simulators. From the simulation, we find out that our proposed scheme is able to reduce communication cost—the number of messages sent—by a minimum of 0.02 and a maximum of 0.30 with an average of 0.18, for varying node densities from 6 to 20, while nonetheless able to retain similar MSL* accuracy rates.
The aim of this research is to apply Throughput Accounting in improving the cost leadership strategy for the woven fabric department (polyester blended - polyester 150/1) in the Waist Textile and Knitting Factory. The problem of the research is that the research sample laboratory does not apply modern cost management methods represented in Throughput Accounting, as the Iraqi economic units suffer from their inability to compete in the labor market in light of the competitive environment. The Ministry of Interior improved the cost leadership strategy for the product of blended polyester and polyester fabrics 1/150. Through the research, a set of conclusions was reached, the most important of which are: Improving the cost lea
... Show MoreMicrofluidic devices provide distinct benefits for developing effective drug assays and screening. The microfluidic platforms may provide a faster and less expensive alternative. Fluids are contained in devices with considerable micrometer-scale dimensions. Owing to this tight restriction, drug assay quantities are minute (milliliters to femtoliters). In this research, a microfluidic chip consisting of micro-channels carved on substrate materials built using an Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO2) laser machine. The CO2 parameters influence the chip’s width, depth, and roughness. To have a regular channel surface, and low roughness, the laser power (60 W), with scanning speed (250 m/s)
... Show MoreManufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L
... Show MoreThe research discusses two variables are important, orientation marketing and quality of service, and that the purpose of the research is to see whether the telecom companies applied orientation marketing or not and to what extent is keen to apply it to suit the Iraqi environment as it has been applied research in kork Telecom company and Asia Cell Telecom are sectors service job in the business sector in Iraq, The information was obtained through the design of the questionnaire compatible runway Likert, and distribution (92) questionnaire, which (50) for the company Korek Telecom and (42) of the Asia-Cell, research population sample included a number of staff in the departments and units in the two companies, it has been support
... Show MoreIn recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne
... Show More<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreBackground: Therapeutic communication is the basis of interactive relationships among nursing team and their children: that affords opportunities to establish rapport, understand the client’s experience, formulate individualized or client interventions and optimize health care resources.
Objectives: The main aim of the study is to determine the Effectiveness of Education Program on Nurses’ Knowledge about Communication Skills with Children.
Methodology: A quasi-experimental study was conducted in Children Welfare Teaching Hospitals from 7th, October 2018 to the 20th, May 2019. The program and instruments have been constructed by the researcher for the purpose of the study. A non- prob
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