Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.
The performance evaluation process requires a set of criteria and for the purpose of measuring the level of performance achieved by the Unit and the actual level of development of its activities, and in view of the changes and of rapid and continuous variables surrounding the Performance is a reflection of the unit's ability to achieve its objectives, as these units are designed to achieve the objectives of exploiting a range of economic resources available to it, and the performance evaluation process is a form of censorship, focusing on the analysis of the results obtained from the achievement All its activities with a view to determining the extent to which the Unit has achieved its objectives using the resources available to it and h
... Show MoreIn aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
... Show MoreCancer is one of the dangerous diseases that afflict a person through injury to cells and tissues in the body, where a person is vulnerable to infection in any age group, and it is not easy to control and multiply between cells and spread to the body. In spite of the great progress in medical studies interested in this aspect, the options for those with this disease are few and difficult, as they require significant financial costs for health services and for treatment that is difficult to provide.
This study dealt with the determinants of liver cancer by relying on the data of cancerous tumours taken from the Iraqi Center for Oncology in the Ministry of Health 2017. Survival analysis has been used as a m
... Show MoreObjective: To identified the relationship between general and spinal Anesthesia upon breastfeeding and (demographic &reproductive) : Comparative Study. Methodology: The present study employs a descriptive comparative design held at the labor and delivery room , operational room for cesarean section and maternity word in maternity department at Al Emamain Al Kadhamain Medical City in Baghdad city. Data collection was initiated on 2nd January to end of March /2014. Purposive sample consisted of (150) mother and her neonate, The study sample divided into three groups:(50) under general anesthesia , (50) under
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
The present study investigates the application of a combined electrocoagulation-electrooxidation (EC-EO) process for the treatment of wastewater generated from Al-Dewaniya petroleum refinery plant in Iraq. The EC-EO process was examined in terms of its ability to simultaneously produce coagulant and oxidant agents by using a parallel plate configuration system composed of stainless steel plates as cathode and pair of aluminum and graphite plates as anode at two different current concentrations (1.92A/l and 0.96A/l). The results showed that the best conditions for treatment of Al-Dewaniya petroleum refinery wastewater using the combined approach were current concentration of (0.96A/l), current density
Wireless sensor network (WSN) security is an important component for protecting data from an attacker. For improving security, cryptography technologies are divided into two kinds: symmetric and asymmetric. Therefore, the implementation of protocols for generating a secret key takes a long time in comparison to the sensor’s limitations, which decrease network throughput because they are based on an asymmetric method. The asymmetric algorithms are complex and decrease network throughput. In this paper, an encryption symmetric secret key in wireless sensor networks (WSN) is proposed. In this work, 24 experiments are proposed, which are encryption using the AES algorithm in the cases of 1 key, 10 keys, 25 keys, and 50 keys. I
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