Leveraging Sensory Data in Estimating Transformer Lifetime

Transformer lifetime assessments plays a vital role in reliable operation of power systems. In this paper, leveraging sensory data, an approach in estimating transformer lifetime is presented. The winding hottest-spot temperature, which is the pivotal driver that impacts transformer aging, is measured hourly via a temperature sensor, then transformer loss of life is calculated based on the IEEE Std. C57.91-2011. A Cumulative Moving Average (CMA) model is subsequently applied to the data stream of the transformer loss of life to provide hourly estimates until convergence. Numerical examples demonstrate the effectiveness of the proposed approach for the transformer lifetime estimation, and explores its efficiency and practical merits.Comment: 2017 North American Power Symposium (NAPS), Morgantown, WV, 17-19 Sep. 201

Digitization of World Heritage Sites of Iran as a Tool for Facilitating Online Access During Worldwide Pandemic: Case Study of Pasargadae World Heritage Site

Purpose Cultural heritage digitization facilitates the preservation of culturally valuable objects, entities, or items into a digital form allowing more comprehensive and concurrent access to such objects. It becomes more significant for overcoming the constraints associated with physical access, especially during turmoil, disasters, and pandemics like COVID-19, where physical interactions are almost restricted. Covid-19 restrictions and resultant social distancing protocols impacted nearly every facet of human life. Galleries, Libraries, Archives, Museums, and heritage sites across the globe were also affected as they were closed for the general public. Therefore, the study explores the importance of making diverse cultural heritage information available online and accessible to the broader user community and provisions for data security through proper backups, setting user privileges, and maintaining necessary updates. Design/Methodology/Approach The study selected Pasargadae world heritage site in Iran as the study area by analyzing the database maintained and available for consultation. Further, the study attempts to highlight the advantages associated with the digitization of cultural items, including manuscripts, images, monuments, sites, etc. It also highlights prerequisites for managing such information online effectively using digitization. Findings Given the state of cultural heritage in Iran, digitization is still in the infancy stage. It is necessary to develop well-equipped policies, technological infrastructures, including high-speed internet, scanning machines, high-resolution digital cameras, and servers with high capacity processing for digitization. Besides, adequate funding and significant management concerns are needed to address various ethical and privacy issues, including copyright concerns associated with Iran’s cultural heritage digitization process. Originality/value The work is a thorough attempt towards surveying Pasargadae world heritage site to understand the basic requirements for creating an online information delivery portal through the digitization of rich cultural heritage sites for enabling access even in virtual mode

Data-Enabled Distribution Grid Management

In 2020, U.S. electric utilities installed more than 94 million advanced meters, which brought the percentage of residential customers equipped with smart meters to 75%. This significant investment allows collecting extensive customer data at the distribution level, however, the data are not currently leveraged effectively to help with system operations. This dissertation aims to use the smart meters’ data to improve the grid’s reliability, stability, and controllability by solving two of the most challenging problems at the distribution level, namely distribution network phase identification and outage identification. Distribution networks have typically been the least observable and most dynamic and locally controlled elements in the power grid. Complete information about the network topology is continuously changing and is not always readily available when needed. Lack of phase connectivity information is a challenge, especially when rebalancing the grid and also in the aftermath of outages caused by extreme events. Traditionally, phase identification is executed manually. In this dissertation, a machine learning-based data mining method for accurate and efficient phase identification of residential customers is proposed by leveraging power consumption data collected through smart meters. The proposed method uses a high-pass filter to remove the redundant and irrelevant segments of the power consumption time series, and accordingly identifies the residential customers’ phase connectivity through a modified clustering algorithm. Accurate connectivity information among customers is essential for outage identification and management in distribution networks. Extreme weather events can cause significant damage to electric power grid infrastructure and lead to widespread power outages. The frequency and the intensity of these events are continuously increasing as a direct result of climate change. Identifying grid components that are damaged is the first step to recovering from extreme weather-related power outages. An effective data mining method in identifying distribution network line outages is presented in this dissertation by leveraging data collected through AMI. The line outage identification method is developed based on a Multi-Label Support Vector Machine (ML-SVM) classification scheme that utilizes the status of customers’ smart meters as input data and identifies the outage/operational status of distribution lines. Numerical simulations demonstrate the effectiveness of the proposed models and their respective viability in achieving the targeted operational objectives

The Effectiveness of Couples' Relationship Enrichment Training with Emotion-Focused Approach on Fear of Intimacy and Insecure Attachment Styles

Background and Aim:Marital infidelity is a traumatic interpersonal issue that can lead to cognitive, emotional, and behavioral symptoms in the victim. Therefore, this study aimed to investigate the effectiveness of couples' relationship enrichment training with the EFT, emotion-focused approach on fear of intimacy and insecure attachment styles among couples  faced with spousal infidelity. Materials and Methods:The method of the study was a semi-experimental with pre-test, post-test, control group and with the follow-up phase. The statistical population of this study was all men and women faced with spousal infidelity in Tehran in 2019-2020.Throughconvenience sampling method, 40 people were selected and randomly divided into an intervention group by training couples' relationship enrichment with an emotion-focused approach and a control group. The experimental group underwent 8 sessions of 90 minutes of training to enrich couples' relationships with an emotion-focused approach and the control group stayed on the waiting list. Data were collected based on an attachment styles questionnaire and fear of intimacy questionnaire. Multivariate covariance analysis test was used to eliminate the effect of pre-test using SPSS software. Results:The results showed that emotion-focused training affected the scores of insecure attachment styles (P<0.01) and fear of intimacy (P<0.01). The results also showed that the method of training was to enrich couples' relationships with an emotion-focused approach in the follow-up phase. Conclusion:It can be concluded that the intervention on  training couples' relationship enrichment focused on the emotion-focused approach is an effective model in women and men affected by spousal infidelity and can be used as one of the therapeutic or educational methods in couple therapy program

COVID-19 PTSD Predicts Positive Effects among Healthcare Professionals in Iran: Investigating the Roles of Self-Efficacy and Resilience in a Follow-Up Study

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Designing Alternative Housing in an Old Context: Zargandeparsh, Tehran

Today, poor performance in old residential contexts in terms of memorable visual elements reduce the residents’ sense of belonging. The study used a combination of qualitative and quantitative research methods. To meet the needs of residents, a questionnaire was distributed among twenty-five experts. Data analysis was performed using fuzzy logic to calculate the weight of each criterion of hierarchical fuzzy (FAHP). According to the findings, the largest weight belonged to social interaction (0.288), physical (0.205) and dependence (0.179). The results showed that social interaction is imperative in increasing the residents’ sense of attachment.© 2016. The Authors. Published for AMER ABRA by e-International Publishing House, Ltd., UK. Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies, Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.Keywords: Housing; old texture; place; sense of attachment

Assessing Awareness Level about Warning Signs of Cancer and its Determinants in an Iranian General Population

The present study was aimed at investigating the awareness level about warning signs of cancer and its determinants in an Iranian general population. This cross-sectional interview-based survey investigated 2,500 people aged 18 years and over, as a representative sample of Tehran population. Latent class regression was applied for analyzing data. A small (18.8%) proportion of the respondents had high level of knowledge, and 54.5% had moderate awareness, and 26.7% had low level of awareness. Most effective predictors for awareness were educational attainment, sex, and marital status. The findings suggest that the overall level of knowledge about warning signs of cancer among the public is low, particularly about some specific signs. Accordingly, educational and intervention programmes, with special attention placed on particular at-risk populations, to increase awareness about the disease leading to its early diagnosis are needed

Evaluation of Leachate Quality and its Effects on Agriculture in the Vicinity of Zanjan Landfill

Landfills can be considered as a potential threat to groundwater resources, considering the potential of groundwater pollution by leachate with the pollutants such as hydrocarbons and heavy metals. In this study, spatial changes in groundwater quality used in agriculture, in the vicinity of landfill site of municipal solid wastes in the southwest of Zanjan city were investigated. For this purpose, analysis of 18 physicochemical, heavy metals and bacterial parameters in leachate and 14 groundwater samples were investigated around the dumpsite up to a 5 km radius from landfill during two sampling periods (i.e., December 2020 and June 2011). In this study, several indices including leachate pollution index, sodium absorption ratio, Killie index, soluble sodium percentage and permeability index were used to investigate groundwater pollution in the study area due to leachate or other sources. According to the results of LPI, none of the groundwater samples were polluted with leachate. Also, the quality of these resources for use in agriculture was evaluated favorably according to SAR, KR and PI indices, however, according to SSP, 64% and 86% of samples during December 2020 and June 2021, respectively, were reported polluted. In general, the results of qualitative study of groundwater samples in dry season (December 2020) were more pronounced than pollutants. Although based on the results of agricultural indicators and LPI in well number 5 as the closest well to the landfill, no contamination by leachate has been reported, however the high chlorine concentration which was at maximum of allowed range, the potential dangers of landfill leachate were shown. It is noted that chlorine acts as a leachate detector in groundwater. Therefore it is recommended that monitoring wells be dug at different depths and at distances of less than one kilometer from the landfill, and sampling be done in successive periods to determine even the smallest effects of leachate on groundwater