Papers by Pooneh Khodabakhsh
Journal of Solar Energy Research, 2018
Wireless sensors networks consist of several tiny battery powered devices which are utilized to m... more Wireless sensors networks consist of several tiny battery powered devices which are utilized to monitor and gather information of desired area, such as a Net Zero Energy Building. As there is no way to recharge the nodes' energy and batteries, efficient energy consumption plays crucial role in prolonging nodes' and network's lifetime. One of the most popular routing protocol is LEACH protocol, which suffers from drawbacks, despite several modifications have been deployed. This research aims to optimize the Leach protocol from three different aspects. Initially, the allocated energy of network is distributed to each nodes based on their distance with base station. The more distance between a node and BS, the more energy portion is allocated to the given node. Secondly, Genetic algorithm has been employed to select optimal cluster head set whose fitness function addresses number of CHs and distance between CHs and the BS. Lastly, sensor nodes are clustered by fuzzy clustering. Comparing the results with previous versions illustrates that the proposed modifications could prolong considering network and improve the energy consumption and the modified LEACH achieves 10% improvement in terms of survival rate of nodes.
Journal of Diabetes & Metabolic Disorders
Background Since its emergence in December 2019, until June 2022, coronavirus 2019 (COVID-19) has... more Background Since its emergence in December 2019, until June 2022, coronavirus 2019 (COVID-19) has impacted populations all around the globe with it having been contracted by ~ 535 M people and leaving ~ 6.31 M dead. This makes identifying and predicating COVID-19 an important healthcare priority. Method and Material The dataset used in this study was obtained from Shahid Beheshti University of Medical Sciences in Tehran, and includes the information of 29,817 COVID-19 patients who were hospitalized between October 8, 2019 and March 8, 2021. As diabetes has been shown to be a significant factor for poor outcome, we have focused on COVID-19 patients with diabetes, leaving us with 2824 records. Results The data has been analyzed using a decision tree algorithm and several association rules were mined. Said decision tree was also used in order to predict the release status of patients. We have used accuracy (87.07%), sensitivity (88%), and specificity (80%) as assessment metrics for our model. Conclusion Initially, this study provided information about the percentages of admitted Covid-19 patients with various underlying disease. It was observed that diabetic patients were the largest population at risk. As such, based on the rules derived from our dataset, we found that age category (51-80), CPR and ICU residency play a pivotal role in the discharge status of diabetic inpatients.
This research aims to predict PV output power by using different neuro-evolutionary methods. The ... more This research aims to predict PV output power by using different neuro-evolutionary methods. The proposed approach was evaluated by a data set, which was collected at 5-minute intervals in the photovoltaic laboratory of Niroo Research Institute of Iran (Tehran). The data has been divided into three intervals based on the amount of solar irradiation, and different neural networks were used for predicting each interval. NSGA II, a multi-objective optimization algorithm, has been applied to search an appropriate set of weights, which optimized the neural network with two or more conflicting objectives. The MLP-NSGA II algorithm provides better results with the Mean Square Error (MSE) and correlation coefficient (R2) of 0.01 and 0.98, respectively, in comparison with Linear Regression, MLP, and MLP-GA. By the way, obtained results show that the precision of prediction models would be improved by reducing input parameters’ time intervals.
PurposeColorectal cancer (CRC) is one of the most fatal cancers in the world. Determining if the ... more PurposeColorectal cancer (CRC) is one of the most fatal cancers in the world. Determining if the risk of polymorphism alleles for CRC could contribute to clinical situations suggestive of an increased genetic risk for CRC is of significant importance. The aim of this study was to evaluate the association of genetic polymorphisms in two genes, APC and MUTYH, with CRC susceptibility in Iranian society. MethodsIn this experimental study, DNA was extracted from 200 blood samples (100 control and 100 patients with CRC). After identifying point mutations in APC and MUTYH genes and designing primers, they were examined by Tetra-arms PCR technique. Chi-square test was used to calculate and analyze the statistical and frequency of SNP in patients and control groups. ResultsSNPs: rs121913333, rs77542170, rs1801166 and rs869312753 showed significant association with CRC. rs121913333 on 5q22 appeared to have the highest degree of correlation with CRC (P=0.0001). ConclusionOur findings indicate ...
Received: 18 June 2018 Accepted: 29 January 2018 Extended Abstract Paper pages (91-104) Introduct... more Received: 18 June 2018 Accepted: 29 January 2018 Extended Abstract Paper pages (91-104) Introduction In recent years, social network analysis gains great deal of attention. Social networks have various applications in different areas, namely predicting disease epidemic, search engines and viral advertisements. A key property of social networks is that interpersonal relationships can influence the decisions that they make. Finding the most influential nodes is important in social networks because such nodes can greatly affect many other people. In this paper, diffusion among nodes is investigated using the centrality of Shapely value and by dividing a network into communities in linear threshold and by the independent cascade model. Furthermore, this algorithm is evaluated by different data sets and compared with benchmarks.
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Papers by Pooneh Khodabakhsh