Nurses’ Knowledge Regarding Heart Failure Education Principles in Erbil Teaching Hospital

Background and objective: Heart Failure is a major public health problem often associated with a decreased quality of life and high mortality rate. To optimize the quality of management and support patients to care for themselves in their own homes, they need to be well-educated about all aspects of the heart failure. This study aims to investigate nurses’ knowledge regarding the treatments that can be taught to heart failure patients to improve self-care. Methods: Cross-sectional study, 64 nurses out of 85 working at three public hospitals in Erbil City took part, the data was collected from 15th February to 15th March 2017 through interviews using a questionnaire schedule. The data was analyzed using Statistical Package for the Social Science (SPSS) program version 20. Results: Majority of the participants were young (87.6% within the range of 21-40), male (62.5%), and graduated with a technical diploma (60.9%). More than half of them (53.1%) have between 1–5 years of nursing experience, 50% of the nurses work in the Surgical Speciality Hospital - Cardiac Centre and 43.8% of them have general knowledge of Cardiac care. The majority of participants achieved a good knowledge score (70.3%). There was a significant association between level of knowledge of nurses working in the Surgical Speciality Hospital - Cardiac Centre and Rizgary Teaching Hospital, while few of them are in Hawler Teaching Hospital (53.3%, 26.7% and 20% respectively P <0.002). Conclusion: The study concluded that the nurses have good knowledge score, but still need continuous knowledge and practical training to educate patients regarding heart failure. High level of significance was found between the levels of knowledge and the working area

Machine Learning Methods for Better Water Quality Prediction

In any aquatic system analysis, the modelling water quality parameters are of considerable significance. The traditional modelling methodologies are dependent on datasets that involve large amount of unknown or unspecified input data and generally consist of time-consuming processes. The implementation of artificial intelligence (AI) leads to a flexible mathematical structure that has the capability to identify non-linear and complex relationships between input and output data. There has been a major degradation of the Johor River Basin because of several developmental and human activities. Therefore, setting up of a water quality prediction model for better water resource management is of critical importance and will serve as a powerful tool. The different modelling approaches that have been implemented include: Adaptive Neuro-Fuzzy Inference System (ANFIS), Radial Basis Function Neural Networks (RBF-ANN), and Multi-Layer Perceptron Neural Networks (MLP-ANN). However, data obtained from monitoring stations and experiments are possibly polluted by noise signals as a result of random and systematic errors. Due to the presence of noise in the data, it is relatively difficult to make an accurate prediction. Hence, a Neuro-Fuzzy Inference System (WDT-ANFIS) based augmented wavelet de-noising technique has been recommended that depends on historical data of the water quality parameter. In the domain of interests, the water quality parameters primarily include ammoniacal nitrogen (AN), suspended solid (SS) and pH. In order to evaluate the impacts on the model, three evaluation techniques or assessment processes have been used. The first assessment process is dependent on the partitioning of the neural network connection weights that ascertains the significance of every input parameter in the network. On the other hand, the second and third assessment processes ascertain the most effectual input that has the potential to construct the models using a single and a combination of parameters, respectively. During these processes, two scenarios were introduced: Scenario 1 and Scenario 2. Scenario 1 constructs a prediction model for water quality parameters at every station, while Scenario 2 develops a prediction model on the basis of the value of the same parameter at the previous station (upstream). Both the scenarios are based on the value of the twelve input parameters. The field data from 2009 to 2010 was used to validate WDT-ANFIS. The WDT-ANFIS model exhibited a significant improvement in predicting accuracy for all the water quality parameters and outperformed all the recommended models. Also, the performance of Scenario 2 was observed to be more adequate than Scenario 1, with substantial improvement in the range of 0.5% to 5% for all the water quality parameters at all stations. On validating the recommended model, it was found that the model satisfactorily predicted all the water quality parameters (R2 values equal or bigger than 0.9). © 201

Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model

Climate change is one of the most effectual variables on the dam operations and reservoir water system. This is due to the fact that climate change has a direct effect on the rainfall&ndash;runoff process that is influencing the water inflow to the reservoir. This study examines future trends in climate change in terms of temperature and precipitation as an important predictor to minimize the gap between water supply and demand. In this study, temperature and precipitation were predicted for the period between 2046 and 2065, in the context of climate change, based on the A1B scenario and the HAD-CM3 model. Runoff volume was then predicted with the IHACRES model. A new, nature-inspired optimization algorithm, named the shark algorithm, was examined. Climate change model results were utilized by the shark algorithm to generate an optimal operation rule for dam and reservoir water systems to minimize the gap between water supply and demand for irrigation purposes. The proposed model was applied for the Aydoughmoush Dam in Iran. Results showed that, due to the decrease in water runoff to the reservoir and the increase in irrigation demand, serious irrigation deficits could occur downstream of the Aydoughmoush Dam

Optimised neural network model for river nitrogen prediction utilizing a new training approach

In the past few decades, there has been a rapid growth in the concentration of nitrogenous compounds such as nitrate-nitrogen and ammonia-nitrogen in rivers, primarily due to increasing agricultural and industrial activities. These nitrogenous compounds are mainly responsible for eutrophication when present in river water, and for ‘blue baby syndrome’ when present in drinking water. High concentrations of these compounds in rivers may eventually lead to the closure of treatment plants. This study presents a training and a selection approach to develop an optimum artificial neural network model for predicting monthly average nitrate-N and monthly average ammonia-N. Several studies have predicted these compounds, but most of the proposed procedures do not involve testing various model architectures in order to achieve the optimum predicting model. Additionally, none of the models have been trained for hydrological conditions such as the case of Malaysia. This study presents models trained on the hydrological data from 1981 to 2017 for the Langat River in Selangor, Malaysia. The model architectures used for training are General Regression Neural Network (GRNN), Multilayer Neural Network and Radial Basis Function Neural Network (RBFNN). These models were trained for various combinations of internal parameters, input variables and model architectures. Post-training, the optimum performing model was selected based on the regression and error values and plot of predicted versus observed values. Optimum models provide promising results with a minimum overall regression value of 0.92

Perbedaan Hasil Belajar Mata Pelajaran Instalasi Motor Listrik Menggunakan Software Simulasi EKTS Dalam Metode Problem Based Learning Dan STAD Pada Siswa Kelas XI TIPTL SMK Negeri 1 Singosari.

ABSTRAK Kurikulum 2013 digagas agar peserta didik berpartisipasi aktif dalam proses pembelajaran. Akan tetapi, dalam observasi di SMK Negeri 1 Singosari ditemukan beberapa masalah yang dihadapi khususnya pada mata pelajaran instalasi motor listrik. Guru masih menggunakan metode konvensional seperti ceramah. Belum lagi pemakaian media yang monoton yaitu dengan menggambarkan rangkaian dipapan tulis sehingga siswa hanya menyalin tulisan tanpa memahami cara kerja rangkaian. Berdasarkan fakta tersebut maka peneliti bermaksud mengadakan penelitian untuk mengetahui cara pengajaran dan penggunaan media yang tepat untuk mengetahui hasil belajar KI-1,2 (sikap), KI-3 (pengetahuan) dan KI-4 (keterampilan) dalam metode pembelajaran yang berbeda. Penggunaan software Elektrik Kumanda Teknikleri Simülatörü (EKTS) dalam pembelajaran problem based learning dan STAD merupakan solusi yang ditawarkan peneliti. Penelitian ini menggunakan rancangan penelitian true eksperimental design. Desain penelitian ini adalah control grup pre test-post test yang terdiri dari kelas kontrol dan eksperimen. Data penelitian berupa paparan data hasil belajar KI-1,2 (sikap), KI-3 (pengetahuan) dan KI-4 (keterampilan) dalam metode pembelajaran problem based learning (PBL) dan student team achivement division (STAD). Pengumpulan data dilakukan dengan soal pilihan ganda,lembar observasi KI-1,2 (sikap) dan KI-4 (keterampilan). Uji prasyarat dilakukan untuk mengetahui agar kedua sampel penelitian layak diuji. Dengan mengetahui tidak ada perbedaan pada kedua kelas kemudian dilakukan analisis hasil. Analisis data yang dilakukan adalah uji normalitas data KI-1,2 (sikap), KI-3 (pengetahuan) dan KI-4 (keterampilan). Uji homogenitas data KI-1,2 (sikap), KI-3 (pengetahuan) dan KI-4 (keterampilan). Dalam peelitian ini data yang dinyatakan normal dan homogen kemudian dilakukan uji beda (uji-t) antara hasil belajara KI-3 (pengetahuan) kelas PBL dan STAD, KI-1,2 (sikap) antara PBL dan STAD, serta KI-4 (keterampilan) kelas PBL dan STAD

The strategy of slang traslation and its meaning equivalence in cobain montage of heck movie subtitle

xi, 42 hlm.; ilus.; 25 cm

The strategy of slang traslation and its meaning equivalence in cobain montage of heck movie subtitle

xi, 42 hlm.; ilus.; 25 cm

Analisis Isi Prototipe Buku Olahraga Rekreasi Paser

Penelitian ini berkonsentrasi untuk menganalisis isi prototipe buku olahraga rekreasi Paser. Waduk Cacaban yang terletak di Kabupaten Tegal merupakan kondisi alam yang dirasa cocok dengan diadakan/dimunculkannya daya tarik baru untuk menarik lebih banyak pengunjung untuk datang, yang berupa olahraga rekreasi Paser. Penelitian ini menggunakan metode penelitian deskriptif. Subjek penelitian adalah ahli olahraga rekreasi paser, ahli pariwisata, ahli olahraga, ahli kebahasaan. Instrument penelitian berupa angket lembar kuisioner terbatas. Tujuan penelitian ini yaitu menganalisis kualitas prototipe buku olahraga rekreasi paser yang kemudian diharapkan dapat digunakan sebagai referensi dalam penyelenggaran paser baik itu bersifat rekreasi maupun kegiatan olahraga rekreasi Paser yang bersifat event. Simpulan dalam penelitian ini adalah produk buku olahraga rekreasi Paser layak digunakan sebagai penunjang kegiatan olahraga rekreasi Paser