Generalised Decision Level Ensemble Method for Classifying Multi-media Data

In recent decades, multimedia data have been commonly generated and used in various domains, such as in healthcare and social media due to their ability of capturing rich information. But as they are unstructured and separated, how to fuse and integrate multimedia datasets and then learn from them eectively have been a main challenge to machine learning. We present a novel generalised decision level ensemble method (GDLEM) that combines the multimedia datasets at decision level. After extracting features from each of multimedia datasets separately, the method trains models independently on each media dataset and then employs a generalised selection function to choose the appropriate models to construct a heterogeneous ensemble. The selection function is dened as a weighted combination of two criteria: the accuracy of individual models and the diversity among the models. The framework is tested on multimedia data and compared with other heterogeneous ensembles. The results show that the GDLEM is more exible and eective

Attitude and knowledge of Iranian female nurses about Human Papilomavirus infection and cervical cancer: a cross sectional survey

Background and aim. Human Papilomavirus (HPV) is one of the most widespread sexually transmitted diseases is highly related to cervical cancer in women. Cervical cancer?s crude incidence rate in Iran is 6-8 per 100,000. The HPV vaccine provides a chance to considerably decrease the transmission of most types of HPV. The aim of this study was to evaluate awareness and knowledge of HPV infection and vaccines and to assess the attitude and approach toward these vaccines among female nurses at Shahid Sadoughi University of Medical Sciences, Yazd, Iran. Materials and methods. This cross-sectional, descriptive study was performed among 380 female nurses. Data were collected using a questionnaire was consisted in demographic variables and questions on knowledge of participants about HPV infection, HPV vaccine and cervical cancer and also questions on attitude of nurses towards HPV vaccination. The validity and internal consistency of questionnaire was confirmed during experts consents and pilot testing (? = 0.79). Data analysis was performed using SPSS15 using ?2-test or Fisher?s exact test. Results. Three hundred and eighty questionnaires were dis- tributed and 357 female nurses completed and returned their questionnaires: Only one hundred and thirty-one of the nurses (36.7%) knew about HPV infection and how it can cause abnor- mal pap Smear results. about 147 (41.2%) of the nurses stated they would want to be vaccinated. About 146 (40.9%) of respond- ents supported vaccination of preadolescent girls. Conclusion. The results of this study confirm the lack of knowledge about HPV vaccine and its relation to cervical cancer and also the ways of this cancer prevention. Our study shows an urgent need to design similar studies in other regions of Iran and draw a broad esti- mation on knowledge of different target groups to make a national program to increase the knowledge of women on this matter and help to decrease the rate of cervical cancer in Iranian population

Changes in Prevalence and Severity of Domestic Violence During the COVID-19 Pandemic:A Systematic Review

Background: To contain the spread of COVID-19, governmental measures were implemented in many countries. Initial evidence suggests that women and men experience increased anger and aggression during COVID-19 lockdowns. Not surprisingly, media reports and initial empirical evidence highlight an increased risk for domestic violence (DV) during the pandemic. Nonetheless, a systematic review of studies utilizing participants' reports of potential changes in DV prevalence and severity during the pandemic as compared to pre-pandemic times is needed.Objective: To examine empirical, peer-reviewed studies, pertaining to the potential change in prevalence and severity of different types of DV during the COVID-19 pandemic, as reported by study participants.Data Sources: Electronic EMBASE, MEDLINE, PsycINFO, and CINAHL searches were conducted for the period between 2020 and January 5, 2022. References of eligible studies were integrated by using a snowballing technique.Study Selection: A total of 22 primary, empirical, peer-reviewed studies published in English or German were included.Results: Of the 22 studies, 19 were cross-sectional whereas 3 included both pre-pandemic and during pandemic assessments. Data synthesis indicates that severity of all types of DV as well as the prevalence of psychological/emotional and sexual DV increased for a significant number of victims in the general population during the pandemic. Evidence for changes in prevalence regarding economic/financial, physical, and overall DV remains inconclusive. There was considerable between-study variation in reported prevalence depending on region, sample size, assessment time, and measure.Conclusions: Data synthesis partly supports the previously documented increase in DV. Governmental measures should consider the availability of easily accessible, anonymous resources. Awareness and knowledge regarding DV need to be distributed to improve resources and clinical interventions

An adaptive version of k-medoids to deal with the uncertainty in clustering heterogeneous data using an intermediary fusion approach

This paper introduces Hk-medoids, a modified version of the standard k-medoids algorithm. The modification extends the algorithm for the problem of clustering complex heterogeneous objects that are described by a diversity of data types, e.g. text, images, structured data and time series. We first proposed an intermediary fusion approach to calculate fused similarities between objects, SMF, taking into account the similarities between the component elements of the objects using appropriate similarity measures. The fused approach entails uncertainty for incomplete objects or for objects which have diverging distances according to the different component. Our implementation of Hk-medoids proposed here works with the fused distances and deals with the uncertainty in the fusion process. We experimentally evaluate the potential of our proposed algorithm using five datasets with different combinations of data types that define the objects. Our results show the feasibility of the our algorithm, and also they show a performance enhancement when comparing to the application of the original SMF approach in combination with a standard k-medoids that does not take uncertainty into account. In addition, from a theoretical point of view, our proposed algorithm has lower computation complexity than the popular PAM implementation

Investigating the Development of Production-economic Relations in the Agricultural Sector of Iran

The agricultural sector in developing countries is the main engine of economic growth and development. Developing countries can go to their agricultural sector to overcome the crisis of underdevelopment, and while trying to expand agricultural production, they are thinking of combining this sector with advanced technologies in order to make their products more efficient. Due to its extensive connections with other economic sectors, this sector can provide the ground for wealth production, market creation, currency exchange and industry growth with its growth. The purpose of this study was to investigate the development of production-economic relations in the agricultural sector of Iran. In this regard, the impact of development policy and growth of the agricultural sector on employment, total economic output and other economic sectors has been evaluated. The methodology of this research has been done with the approach of input and output table and social accounting matrix. The analysis is based on the approach of technical coefficients, Leontief coefficients, backward and forward linkages and employment coefficients. Results show that there are strong linkages between the "Agriculture and Horticulture" and "Livestock and Fisheries" sectors and the "Agriculture and Horticulture" sector has a strong and rapid impact on the final demand of the "Chemical Industries" sector as well as the "Livestock and "Fishing" has had a strong and rapid impact on the final demand of the "Livestock and Fisheries" sector. The backward and forward linkages of the agriculture section in the economy are at a moderate level and this sector has a high coefficient and potential in job creation and in line with strategies to reduce unemployment with lower investment has the ability to create high employment

Comparative evaluation of visual estimation and accurate measurement of the amount of blood loss during surgery

Background: The greater the ability to accurately estimate the amount of blood loss during surgery, the greater the readiness to deal with possible risks during surgery. Therefore, in this study, we aimed to compare the visual estimation and accurate measurements of the amount of blood loss during surgery in order to make better management of the bleeding during surgery and make proper cares in proper time. Methods: 31 patients undergoing surgery who referred to Firoozgar hospital in Tehran, Iran, in 2017 were entered this clinical trial study using simple sampling method. All patients underwent posterior spinal fusion (PSF) surgery. Then, the amount of bleeding during the operation was calculated in two ways: visual estimation and also using a sensitive scale. Data were analyzed via SPSS software using descriptive statistics and Wilcoxon test. Findings: The mean age of the participants was 41.4 years old, and the mean weight was 65.2 kg. There was a significant difference between the amount of bleeding calculated as a visual bleeding amount and the bleeding calculated by sensitive scale at the first hour of operation (P < 0.0001), and also at the second hour of operation (P < 0.0001). Conclusion: The amount of blood on the gauzes calculated by visual estimation was significantly lower than the actual estimation. In order to reduce this error, it is recommended that, in assessing the amount of blood on gauzes, in addition to the amount of gauze to be impregnated with the blood, the amount of moisture (moisture) of the gauzes should also be taken into account. © 2019, Isfahan University of Medical Sciences(IUMS). All rights reserved

Impact of the COVID-19 Pandemic On Violence Against Children: A Narrative Review.

The goal of this paper was to explore the different ways the COVID-19 pandemic has affected violence against children (VAC). Recent research of peer-reviewed articles using operational or survey data revealed the pandemic's impact in terms of institutional responses, risk and mediating factors, changes in VAC dynamics, and a likely increase in child marriage. Findings include a decrease in institutional responses, activities, and prevention case openings; an increased incidence of interparental intimate partner violence (IPV) witnessing cases, hospital admissions for suspected Abusive Head Trauma (AHT), other pediatric injuries, and sexual violence; a change in family conflict dynamics; and an estimated increase in child marriages. It also revealed mediating factors between the relationship of the pandemic and VAC (such as parental stress and mental health symptoms), as well as risk factors observed by service providers, which include the risk of mental health symptoms of both parents and children. Post-pandemic VAC research can be improved by utilizing operational or survey data in a meaningful way to be able to derive sound intervention approaches to diminish the pandemic's impact on VAC and child marriage. We also propose for researchers to integrate child marriage into the definition of VAC