Segregation Dynamics with Reinforcement Learning and Agent Based Modeling

Societies are complex. Properties of social systems can be explained by the interplay and weaving of individual actions. Incentives are key to understand people's choices and decisions. For instance, individual preferences of where to live may lead to the emergence of social segregation. In this paper, we combine Reinforcement Learning (RL) with Agent Based Models (ABM) in order to address the self-organizing dynamics of social segregation and explore the space of possibilities that emerge from considering different types of incentives. Our model promotes the creation of interdependencies and interactions among multiple agents of two different kinds that want to segregate from each other. For this purpose, agents use Deep Q-Networks to make decisions based on the rules of the Schelling Segregation model and the Predator-Prey model. Despite the segregation incentive, our experiments show that spatial integration can be achieved by establishing interdependencies among agents of different kinds. They also reveal that segregated areas are more probable to host older people than diverse areas, which attract younger ones. Through this work, we show that the combination of RL and ABMs can create an artificial environment for policy makers to observe potential and existing behaviors associated to incentives.Comment: 14 pages, 4 figures + supplemental material, in revie

Ensemble of Convolutional Neural Networks for Classification of Breast Microcalcification from Mammograms

Human level recall performance in detecting breast cancer considering microcalcifications from mammograms has a recall value between 74.5% and 92.3%. In this research, we approach to breast microcalcification classification problem using convolutional neural networks along with various preprocessing methods such as contrast scaling, dilation, cropping etc. and decision fusion using ensemble of networks. Various experiments on Digital Database for Screening Mammography dataset showed that preprocessing poses great importance on the classification performance. The stand-alone models using the dilation and cropping preprocessing techniques achieved the highest recall value of 91.3%. The ensembles of the stand-alone models surpass this recall value and a 97.3% value of recall is achieved. The ensemble having the highest F1 Score (harmonic mean of precision and recall), which is 94.5%, has a recall value of 94.0% and a precision value of 95.0%. This recall is still above human level performance and the models achieve competitive results in terms of accuracy, precision, recall and F1 score measures

Optimizing age of information on real-life TCP/IP connections through reinforcement learning

Age of Information (AoI) has emerged as a performance metric capturing the freshness of data for status-update based applications ( e.g. , remote monitoring) as a more suitable alternative to classical network performance indicators such as throughput or delay. Optimizing AoI often requires distinctly novel and sometimes counter-intuitive networking policies that adapt the rate of update transmissions to the randomness in network resources. However, almost all previous work on AoI to data has been theoretical, assuming idealized networking models, and known delay and service time distributions. It is difficult to obtain these statistics and optimize for them in a real-life network as there are many interacting phenomena in different networking layers ( e.g. , consider an end-to-end IoT application running over the Internet). With this work we introduce a deep reinforcement learning-based approach that can learn to minimize the AoI with no prior assumptions about network topology. After evaluating the learning model on an emulated network, we have shown that the method can be scaled up to any realistic network with unknown delay distribution

Solar Power Generation Analysis and Forecasting Real-World Data Using LSTM and Autoregressive CNN

Generated power of a solar panel is volatile and susceptible to environmental conditions. In this study, we have analyzed variables affecting the generated power of a 17.5 kW real-world solar power plant with respect to five independent variables over the generated power: irradiance, time of measurement, panel's temperature, ambient temperature and cloudiness of the weather at the time of measurement. After our analysis, we have trained three different models to predict intra-day solar power forecasts of the plant. Our models are able to predict future power output of the solar power plant with less than 10% RMSE without requiring additional sensor data, e.g. a camera to observe clouds. Based on our forecasting accuracy, our study promises: fast, scaleable and effective solutions to solar power plant maintainers and may facilitate grid safety on a large scale

Linking COVID-19 perception with socioeconomic conditions using Twitter data

We, as humans, are constantly in relation with our environment. Sudden changes in our living media may alter the way we perceive ourselves and our environment in various ways. Coronavirus (COVID-19) outbreak is a great example of a sudden change. The outbreak influenced means of work, study, socialization, and communication in unprecedented ways. In our study, we investigate the topic dynamics of Twitter content sharing for the Republic of Turkey. We have analyzed 1.3 million tweets containing the keyword ``korona'' shared between February 24, 2020 and May 2, 2020. Our study has three key outcomes. The first one is, after the official announcement of first COVID-19 case in Turkey, rate of COVID-19-related content sharing decreases and hygiene-, lifestyle-, and anxiety-related tweets increase. Second, we see that a number of friends and followers influence content sharing dynamics where accounts sharing COVID-19 News-related content have more followers compared to accounts that share the remaining contents. Finally, motivated by the World Bank's Poverty Monitoring Technical Note, we inquired the effect of income on content sharing and found that GDP per capita of the author's city is more influential on COVID-19 News-related content sharing compared to the population and COVID-19 cases per 1,00,000 people. The lower the GDP per capita, the higher the COVID-19 News-related content sharing is. Also, our model indicates that lower income and population along with high rates of COVID-19 cases per 1,00,000 people are associated with increased COVID-19 News-related content sharing

Pre-treatment with nanofiltration (NF) in seawater desalination-Preliminary integrated membrane tests in Urla, Turkey

In this study, the applicability of nanofiltration (NF) was investigated as a pre-treatment stage of reverse osmosis (RO) process for seawater desalination. The desalination performance of such integrated system was checked. Previously, NF (NF90 and NF270) and SWRO (SW30) membranes were used individually in the close-loop operation. Next, the NF permeate was collected using NF membrane by a continuous operation and then this permeate was used as a feed for a closed-loop SWRO system. The performances of single SWRO, NF and NF+RO integrated systems were compared in terms of permeate qualities and quantities. The results showed that permeate recovery of NF270 membrane was higher than that of NF90 membrane. However, the salt rejection of NF90 membrane was better than that of NF270. The single SW30-RO membrane showed an average rejection of 98.2% for salinity, while the permeate recovery value was only 28% at 55bar. Also the average permeate flux of single SW30-RO membrane was 30.1L/hm2. For the integrated system experiments, the highest permeate flux was found with NF90 (30bar)+SW30-RO (40bar) combination. Similar permeate flux values were obtained with single SW30-RO and NF90 (30bar)+SW30-RO (30) bar combination. The lowest permeate flux was found with NF270 (30bar)+SW30-RO (40bar) combination. Salinity was also highly rejected by all integrated system combinations. Permeate recovery values of integrated system combinations showed similar trend with permeate flux. Regarding permeate quality, it was seen that all integrated system combinations were better than single SW30-RO membrane. It was obtained that the permeate quality with NF90+SW30-RO combination was better than that with NF270+SW30-RO combination. © 2015 Elsevier B.V.Ege Üniversitesi: 2013-FEN-061This study was financially supported by the Aliye USTER Foundation and partly by Ege University (Project No. 2013-FEN-061 ). Also, we would like to thank Ege University, Faculty of Fisheries for the kind support to perform our desalination tests in Urla. We thank M. Akçay for AAS analyses. -

Management of Labor Complicated with Extensive Uterine Prolapse

Management of severe uterine prolapsus during active labor is challenging. Detrimental complications are inevitable unless preventive measures have been taken. Active labor may result with uneventful vaginal delivery, nevertheless impeded cervical dilation, cervical dystocia and obstructive labor are all potential outcomes. Enlarged and edematous cervix accompanying prolapse in such cases may obstruct course of labor and may result with dystocia. In this instance, C-section stands as feasible and safe option for both mother and the fetus. Also, it is more likely to provide normal anatomic texture during C-section with effective prolapse reduction. Moreover, spontaneous resolution of the uterine prolapse is possible following C-section and considering suspension procedures till complete recovery of the pelvic anatomy seems reasonable. In this case report, succesful management of an active labor complicated with extensive uterus prolapse have been described along with current literature findings

Performances of some NF and RO membranes for desalination of MBR treated wastewater

WOS: 000431407000023In recent years, because of both lowered discharge limits and reduction of usable water sources, reutilization of water became inevitable. This situation makes the application of advanced water treatment technologies compulsory. In this study, applicability of nanofiltration (NF) and reverse osmosis (RO) methods was investigated for reuse of industrial wastewater treated with advanced treatment method at organized industrial zone. For this purpose, two NF (HL-GE and DL-GE) and one RO (AG-BWRO) membranes were used at 10 bar of applied pressure. Permeability test revealed that HL membrane exhibited the highest permeability with 7.22 +/- 0.79 L/m(2) h bar of permeability constant followed by AG membrane with a permeability constant of 6.03 +/- 0.25 L/m(2) h bar. Less permeable membrane was DL with a permeability constant of 2.08 +/- 0.11 L/m(2) h bar. In terms of rejection performance, conductivity, salinity, chemical oxygen demand (COD), total organic carbon (TOC), color, divalent ions (Ca2+, Mg2+ and SO42-) and monovalent ions (Na+, K+, Cl- and HCO3-) were rejected by HL membrane with an average rejection of 37.2 +/- 2.1%, 38.6 +/- 2.5%, 72.5 +/- 5.5%, 79.9 +/- 6.1%, 85.4 +/- 1.2%, 86.0 +/- 0.5%, 88.8 +/- 0.3%, 99.9 +/- 0.0%, 46.0 +/- 0.9%, 27.0 +/- 0.3% 17.9 +/- 1.1%, 64.3 +/- 2.8%, respectively. The respective rejections by DL membrane were 31.1 +/- 0.8%, 31.2 +/- 1.1%, 36.8 +/- 16.4%, 68.2 +/- 7.3%, 81.0 +/- 4.0%, 77.9 +/- 0.7%, 84.7 +/- 07%, 99.9 +/- 0.0%, 41.0 +/- 04%, 18.4 +/- 1.7%, 14.0 +/- 1.3%, and 45.2 +/- 2.7%. On the other hand, higher water quality was obtained with AG-BWRO membrane. AG-BWRO achieved conductivity, salinity, COD, TOC and color rejections of 96.8 +/- 0.2%, 96.9 +/- 0.1%, 74.7 +/- 2.8%, 90.5 +/- 4.8% and 87.6 +/- 1.9%, respectively. Divalent ions and monovalent ions were rejected by AG-BWRO membrane with an average rejection of higher than 94%. In conclusion, AG-BWRO membrane was found to be the best membrane considering both product water quality and quantity. DL membrane was found to be the worst one among the three membranes investigated in this work. (C) 2017 Published by Elsevier Ltd.Ministry of Science, Industry and Technology of Turkish Republic [0330.STZ.2013-2]; Ege University Scientific Research ProjectsEge University [EU-13-SUF-004]This study has been supported by Ministry of Science, Industry and Technology of Turkish Republic (Project No. 0330.STZ.2013-2) and partly by Ege University Scientific Research Projects (EU-13-SUF-004). We thank ITOB-OSB for the kind support for providing us with water samples. We thank M.Akcay, Y.Soyoglu, S.Ozgoz, C.Kaya, B.Ogla, O.Ustun for their supports

Investigation of mini pilot scale MBR-NF and MBR-RO integrated systems performance-Preliminary field tests

WOS: 000431401200010Recovery of wastewater has become compulsory due to the reasons like lowered discharge limits, pollution of water resources, and increasing water cost depending on the population growth and increasing water use. Even though membrane bioreactor (MBR) processes seem to be an alternative solution providing high quality output water, still, another treatment process after MBR might be essential to be able to use obtained water as irrigation water or process water. In this study, applicability of nanofiltration (NF) and reverse osmosis (RO) methods for reuse of industrial wastewater treated with advanced treatment method at Organized Industrial Zone (OIZ) is investigated. Studies have been implemented with the mini pilot-scale spiral wound NF/RO system installed at OIZ, under applied pressure of 10 bar. For this purpose, NF membrane (NF90-2540 DOW Filmtec) and RO membrane (BW30-2540 DOW Filmtec) were used. According to results obtained, NF90 permeate flux is higher than that of BW30 membrane from December to August. The maximum water recovery obtained with NF90 was about 52.5% while BW30 achieved a maximum water recovery of 44.5%. From September to November, NF90 and BW30 membranes showed similar performances in water recovery as a result of membrane fouling/scaling. NF90 membrane performed rejection percentages of analyzed parameters in the range of 80-100% while the rejection efficiencies of BW30 membrane were in the range 83-100%. Moreover, in comparison of permeate water of NF90 and BW30 membranes with the irrigation water standards; product water qualities of these membranes were found to be suitable for irrigation. According to Turkish water quality classification, first class water quality was produced with BW30 and NF90 membranes except chloride concentration for NF90 membrane. (C) 2016 Elsevier Ltd. All rights reserved.Ministry of Science, Industry and Technology of Turkish Republic [SANTEZ: 0330.STZ.2013-2]This study has been supported by Ministry of Science, Industry and Technology of Turkish Republic (SANTEZ: 0330.STZ.2013-2). We thank ITOB-OSB for the kind support for our field tests. We thank M.Akcay, Y. Soyoglu, S. Ozgoz, C.Kaya, B.Ogla, O.Ustun for their kind supports