Search results for: call drop probability

Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

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Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

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Authors: Marianne Dæhlen

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Periods of apprenticeships are characteristic of many vocational educational training (VET) systems. In many countries, becoming a skilled worker implies that the journey starts with an application for apprenticeships at a company or another relevant training establishment. In Norway, where this study is conducted, VET students start their journey with two years of school-based training before applying for two years of apprenticeship. Previous research has shown that access to apprenticeships differs by family background (socio-economic, immigrant, etc.), gender, school grades, and region. The question we raise in this study is whether the status, reputation, or position of the vocational school contributes to VET students’ access to apprenticeships. Data and methods: Register data containing information about schools’ and VET students’ characteristics will be analyzed in multilevel regression analyses. At the school level, the data will contain information on school size, shares of immigrants and/or share of male/female students, and grade requirements for admission. At the VET-student level, the register contains information on e.g., gender, school grades, educational program/trade, obtaining apprenticeship or not. The data set comprises about 3,000 students. Results: The register data is expected to be received in November 2024 and consequently, any results are not present at the point of this call. The planned article is part of a larger research project granted from the Norwegian Research Council and will, accordingly to the plan, start up in December 2024.

Keywords: apprenticeships, VET-students’ characteristics, vocational schools, quantitative methods

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Hanan M. Alghamdi, Kholud E. Alsalami, Manal I. Alshaikhi, Nouf M. Alsalami, Sara A. Awad, Ruqaya A. Alrabei

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Tourism in Saudi Arabia is one of the emerging sectors with rapid growth. The Kingdom of Saudi Arabia is characterized by its wonderful and historical areas, which constitute important cultural and tourist landmarks. These landmarks attract the attention of the government of Saudi Arabia; hence the improvement of the tourism sector becomes one of the important axes of Saudi Arabia's vision 2030. There is a need to enhance the tourist experience by facilitating the tourism process for visitors to the Kingdom of Saudi Arabia. This project aims to design an application to serve domestic tourists and visitors from outside the Kingdom of Saudi Arabia. This application will contain an automated tourist generate plan service by sentiment analysis of comments in Google Map using Lexicon for method Rule-based approach. There are thirteen regions in the kingdom of Saudi Arabia. The regions supported in this application will be Makkah and Asir regions. According to the output of the sentiment analysis, the application will recommend restaurants and cafes, activities (parks, museums) and shopping (shopping centers) in the generated plan. After that, the system will show the user a drop-down list of “Mega-events in Saudi Arabia” containing a link to the site of events in the Kingdom of Saudi Arabia. and “important information for you” public decency regulations.

Keywords: tourist automated plan, sentiment analysis, comments in google map, tourism in Saudi Arabia

Procedia PDF Downloads 143

Authors: Naime Boudemagh, Zoheir Hammoudi

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The parameters estimation of the K-distribution is an essential part in radar detection. In fact, presence of interfering targets in reference cells causes a decrease in detection performances. In such situation, the estimate of the shape and the scale parameters are far from the actual values. In the order to avoid interfering targets, we propose an Automatic Censoring (AC) algorithm of radar interfering targets in K-distribution. The censoring technique used in this work offers a good discrimination between homogeneous and non-homogeneous environments. The homogeneous population is then used to estimate the unknown parameters by the classical Method of Moment (MOM). The AC algorithm does not need any prior information about the clutter parameters nor does it require both the number and the position of interfering targets. The accuracy of the estimation parameters obtained by this algorithm are validated and compared to various actual values of the shape parameter, using Monte Carlo simulations, this latter show that the probability of censing in multiple target situations are in good agreement.

Keywords: parameters estimation, method of moments, automatic censoring, K distribution

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Authors: A. B. Robert, Adam Pramadia, Calvin Andika

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The main purpose of this study is to explore consumer loyalty characteristic of mobile phone category in Indonesia. Second, this research attempts to identify consumer segment and to explore their profile in each segment as the basis of marketing strategy formulation. This study used some tools of multivariate analysis such as discriminant analysis and cluster analysis. Discriminate analysis used to discriminate consumer loyal and not loyal by using particular variables. Cluster analysis used to reveal various segment in mobile phone category. In addition to having better customer understanding in each segment, this study used descriptive analysis and cross tab analysis in each segment defined by cluster analysis. This study expected several findings. First, consumer can be divided into two large group of loyal versus not loyal by set of variables. Second, this study identifies customer segment in mobile phone category. Third, exploring customer profile in each segment that has been identified. This study answer a call for additional empirical research into different product categories. Therefore, a replication research is advisable. By knowing the customer loyalty characteristic, and deep analysis of their consumption behavior and profile for each segment, this study is very advisable for high impact marketing strategy development. This study contributes body of knowledge by adding empirical study of consumer loyalty, segmentation analysis in mobile phone category by multiple brand analysis.

Keywords: customer loyalty, segmentation, marketing strategy, discriminant analysis, cluster analysis, mobile phone

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Authors: Ikenna Michael Onuorah

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The relentless march of globalization in architecture has led to a homogenization of built environments, often characterized by an overreliance on imported, resource-intensive materials and a disregard for local cultural contexts. This research posits that such practices pose significant environmental and cultural perils, trapping communities in "caged concrete jungles" devoid of both ecological sustainability and a meaningful connection to their heritage. Through a mixed-method approach encompassing quantitative and qualitative data analysis, the study investigated the impacts of neglecting local materials and cultural expression in architectural design. The research is anticipated to yield significant insights into the multifaceted consequences of neglecting locally available materials and cultural expression in architecture. It creates a compelling case for reasserting local materials and cultural expression in architectural design. Based on the anticipated research findings, the study proposed series of actionable recommendations for architects, policymakers, and communities to promote sustainable and culturally sensitive built environments. This will serve as a wake-up call, urging architects, policymakers, and communities to break free from the confines of "caged concrete jungles" and embrace a more sustainable and culturally sensitive approach to design.

Keywords: sustainability, cultural identity, building materials, sustainable dsigns

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Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

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We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: attractor , cardiac, entropy, holter, mathematical , prediction

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Authors: Feddal Imene, Boumediene Youssra, Mimanne Goussem

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The history of the environment and its chemistry is above all the history of its pollution. For a large part, it is the changes made in the air, water and soil by human beings. From there, we can define that pollution is an unfavorable modification of the natural environment that appears as a by-product of human action, through direct and indirect effects. The protection and preservation of the environment is one of the pillars of sustainable development, which is currently a major issue for the future of man and the planet. Currently, humanity is facing an alarming increase in the pollution of the natural environment by various organic or inorganic materials. The objective of our work is to study the adsorption of a textile dye which is known in the industrial environment, methyl green, on raw calcic clay. Our material was characterized by X-ray diffraction (XRD) Fourier transform infrared (FTIR), we also determined its cation exchange capacity (CEC), pHzc and specific surface by Methylene Blue method. The kinetic and thermodynamic study of the adsorption of methyl green was studied, these experiments resulted that the adsorption of the dye follows pseudo second order kinetics, and according to the thermodynamic study and the study of the probability we can say that we have a physisorption.

Keywords: calcic clay, dye, materials, environment

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Authors: Rizwana Amin, Afshan Afroze Bhatti

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The study was a quasi-experimental pre-post test design including two groups. Data was collected from 127 students through non-probability random sampling from Bahaudin Zakariya University Multan. The groups were given pre-test using perceived stress scale and information about academic achievement was taken by self-report. After screening, 27 participants didn’t meet the criterion. Remaining 100 participants were divided into two groups (experimental and control). Further, 4 students of experimental group denied taking intervention. Then 46 understudies were separated into three subgroups (16, 15 and 15 in each) for training. The experimental groups were given the stress management training, each of experimental group attended one 3-hour training sessions separately while the control group was only given pre-post assessment. The data were analyzed using ANCOVA method (analysis of covariance) t–test. Results of the study indicate that stress training will lead to increased emotional intelligence and academic achievement of students.

Keywords: stress, stress management, academic achievement, students

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Authors: Ifeyinwa Orakwe, Ngozi Nwogu, Edward Gobina

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This work presents experimental results relating to the structural characterization of a commercially available alumina membrane. A γ-alumina mesoporous tubular membrane has been used. Nitrogen adsorption-desorption, scanning electron microscopy and gas permeability test has been carried out on the alumina membrane to characterize its structural features. Scanning electron microscopy (SEM) was used to determine the pore size distribution of the membrane. Pore size, specific surface area and pore size distribution were also determined with the use of the Nitrogen adsorption-desorption instrument. Gas permeation tests were carried out on the membrane using a variety of single and mixed gases. The permeabilities at different pressure between 0.05-1 bar and temperature range of 25-200oC were used for the single and mixed gases: nitrogen (N2), helium (He), oxygen (O2), carbon dioxide (CO2), 14%CO₂/N₂, 60%CO₂/N₂, 30%CO₂/CH4 and 21%O₂/N₂. Plots of flow rate verses pressure were obtained. Results got showed the effect of temperature on the permeation rate of the various gases. At 0.5 bar for example, the flow rate for N2 was relatively constant before decreasing with an increase in temperature, while for O2, it continuously decreased with an increase in temperature. In the case of 30%CO₂/CH4 and 14%CO₂/N₂, the flow rate showed an increase then a decrease with increase in temperature. The effect of temperature on the membrane performance of the various gases is presented and the influence of the trans membrane pressure drop will be discussed in this paper.

Keywords: alumina membrane, Nitrogen adsorption-desorption, scanning electron microscopy, gas permeation, temperature

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: WonHo Lee, Hyo-Gyoung Kwak

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A numerical model considering slip behavior of steel-concrete composite structure is introduced. This model is based on a linear bond stress-slip relation along the interface. Single node was considered at the interface of steel and concrete member in finite element analysis, and it improves analytical problems of model that takes double nodes at the interface by adopting spring elements to simulate the partial interaction. The slip behavior is simulated by modifying material properties of steel element contacting concrete according to the derived formulation. Decreased elastic modulus simulates the slip occurrence at the interface and decreased yield strength simulates drop in load capacity of the structure. The model is verified by comparing numerical analysis applying this model with experimental studies. Acknowledgment—This research was supported by a grant(13SCIPA01) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport(MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement(KAIA) and financially supported by Korea Ministry of Land, Infrastructure and Transport(MOLIT) as U-City Master and Doctor Course Grant Program.

Keywords: bond-slip, composite structure, partial interaction, steel-concrete structure

Procedia PDF Downloads 178

Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Jongwan Eun, Sam Helwany, Lakshyana K. C.

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The United Arab Emirates (UAE) is significantly dependent on desalinated water and groundwater resource, which is expensive and highly energy intensive. Despite the scarce water resource, stagnates only 54% of the recycled water was reused in 2012, and due to the lack of infrastructure to reuse the recycled water, the portion is expected to decrease with growing water usage. In this study, an “Oasis” complex comprised of Sustainable Farming Compartments (SFC) was proposed for reusing treated wastewater. The wastewater is used to decrease the ambient temperature of the SFC via an evaporative cooler. The SFC prototype was designed, built, and tested in an environmentally controlled laboratory and field site to evaluate the feasibility and effectiveness of the SFC subjected to various climatic conditions in Abu Dhabi. Based on the experimental results, the temperature drop achieved in the SFC in the laboratory and field site were5 ̊C from 22 ̊C and 7- 15 ̊C (from 33-45 ̊C to average 28 ̊C at relative humidity < 50%), respectively. An energy simulation using TRNSYS was performed to extend and validate the results obtained from the experiment. The results from the energy simulation and experiments show statistically close agreement. The total power consumption of the SFC system was approximately three and a half times lower than that of an electrical air conditioner. Therefore, by using treated wastewater, the SFC has a promising prospect to solve Abu Dhabi’s ecological concern related to desertification and wind erosion.

Keywords: ecological farming system, energy simulation, evaporative cooling system, temperature, treated waste water, temperature

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Authors: Debangana Mukherjee

Abstract:

This study delves into the pivotal role of parenting styles in shaping the development of aggression and empathy in children aged 10 to 12. Using a sample of 300 school students, we employed self-assessment questionnaires and scales to investigate correlations between parenting styles—authoritative, authoritarian, permissive, and neglectful—and behavioural traits, focusing on aggression and empathy as primary outcomes. The findings underscore the intricate relationships between parenting styles, aggressive behaviours, and empathetic tendencies. Notably, certain parenting approaches demonstrated strong correlations with specific behavioural outcomes. For instance, authoritarian parenting showed associations with increased aggression and reduced empathy, while authoritative parenting exhibited the opposite trend. These correlations emphasize the potential impact of parenting styles on children's behavioural development during this critical transitional phase. However, this study is limited by its correlational nature, which does not imply causation. The complexities of human behaviour, the limited scope of analysis, and the need for further research into causative relationships and cultural influences call for a nuanced understanding of these dynamics. Moving forward, longitudinal studies, causality investigations, consideration of cultural diversity, and exploration of additional variables could enrich our understanding of the interplay between parenting styles, empathy, and aggression. Validating these findings across diverse populations and refining interventions could pave the way for nurturing healthy behavioural development in children.

Keywords: aggression, correlational nature, empathy, longitudinal studies, parenting style

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Authors: Yiqi Wu, Simon Tait, Andrew Nichols

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Management of UK railway drainage assets is challenging due to the large amounts of historical assets with long asset life cycles. A major concern for asset managers is to maintain the required performance economically and efficiently while complying with the relevant regulation and legislation. As the majority of the drainage assets are buried underground and are often difficult or costly to examine, it is important for asset managers to understand and model the degradation process in order to foresee the upcoming reduction in asset performance and conduct proactive maintenance accordingly. In this research, a Markov chain approach is used to model the deterioration process of rail drainage assets. The study is based on historical condition scores and characteristics of drainage assets across the whole railway network in England, Scotland, and Wales. The model is used to examine the effect of various characteristics on the probabilities of degradation, for example, the regional difference in probabilities of degradation, and how material and shape can influence the deterioration process for chambers, channels, and pipes.

Keywords: deterioration, degradation, markov models, probability, railway drainage

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Authors: Andriy Didenko, Zanin Kavazovic

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Engineering students often have certain difficulties in mastering major theoretical concepts in mathematical courses such as differential equations. Student projects were proposed to motivate students’ learning and can be used as a tool to promote students’ interest in the material. Authors propose a student project that includes the use of Microsoft Excel. This instructional tool is often overlooked by both educators and students. An integral component of the experimental part of such a project is the exploration of an interactive spreadsheet. The aim is to assist engineering students in better understanding of Euler’s method. This method is employed to numerically solve first order differential equations. At first, students are invited to select classic equations from a list presented in a form of a drop-down menu. For each of these equations, students can select and modify certain key parameters and observe the influence of initial condition on the solution. This will give students an insight into the behavior of the method in different configurations as solutions to equations are given in numerical and graphical forms. Further, students could also create their own equations by providing functions of their own choice and a variety of initial conditions. Moreover, they can visualize and explore the impact of the length of the time step on the convergence of a sequence of numerical solutions to the exact solution of the equation. As a final stage of the project, students are encouraged to develop their own spreadsheets for other numerical methods and other types of equations. Such projects promote students’ interest in mathematical applications and further improve their mathematical and programming skills.

Keywords: student project, Euler's method, spreadsheet, engineering education

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Authors: Isaac Dery

Abstract:

Masculinity studies have gained much purchase globally in recent decades, especially the sense in which they have produced discursive space for interdisciplinary investigations. In the light of this, there is increasing consensus among commentators that different masculinities co-exist within a particular social space. There is also a growing recognition and awareness of the merits in examining the conceptual underpinnings of masculinity (especially hegemonic masculinity) its variously contested meanings, and values, and how it contributes to violent behaviours by men. The consequences of hegemonic masculinity and its violent and traumatic impacts on men and women have been evident. The emerging call to imagine more egalitarian and complex masculinities among men has been at the centre of various discussions on the fight against violence. Some theorists argue that this violence emanates from men’s drive to live up to impossible ideals of “masculinity.” Seeking to make the connections between masculinity and gender-based violence, this paper discusses the imperative and possibilities of engaging men/boys as key actors in the campaign against violence. It is worth re-examining the ways in which men’s embodiment and performance of dangerous masculinities contribute towards violence. This paper therefore argues that empowering men to understand the implications of certain behaviours is the key in an attempt to arrest violence and its traumatic cost. This paper is situated within the thesis that there is a relationship between men’s embodiment and performance of dominant forms of masculinities, on the one hand, and violence against women and other men, on the other. Based on research conducted in northern Ghana on domestic violence, it is the argument of this paper that in order to contain violence against women, conditions of gender construction need to be problematized in a manner that will transform fundamental understandings of gender relations in society.

Keywords: violence against women, masculinities, Ghana, gender

Procedia PDF Downloads 499

Authors: Debangana Mukherjee

Abstract:

This study delves into the pivotal role of parenting styles in shaping the development of aggression and empathy in children aged 10 to 12. Using a sample of 300 school students, we employed self-assessment questionnaires and scales to investigate correlations between parenting styles—authoritative, authoritarian, permissive, and neglectful—and behavioural traits, focusing on aggression and empathy as primary outcomes. The findings underscore the intricate relationships between parenting styles, aggressive behaviours, and empathetic tendencies. Notably, certain parenting approaches demonstrated strong correlations with specific behavioural outcomes. For instance, authoritarian parenting showed associations with increased aggression and reduced empathy, while authoritative parenting exhibited the opposite trend. These correlations emphasize the potential impact of parenting styles on children's behavioural development during this critical transitional phase. However, this study is limited by its correlational nature, which does not imply causation. The complexities of human behaviour, the limited scope of analysis, and the need for further research into causative relationships and cultural influences call for a nuanced understanding of these dynamics. Moving forward, longitudinal studies, causality investigations, consideration of cultural diversity, and exploration of additional variables could enrich our understanding of the interplay between parenting styles, empathy, and aggression. Validating these findings across diverse populations and refining interventions could pave the way for nurturing healthy behavioural development in children.

Keywords: aggression, correlational nature, empathy, longitudinal studies, parenting style

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Authors: A. Movaghar, R. A. Mahdavinejad

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To analyze the effect of various parameters of fluid on the material properties such as surface and depth defects and/or cracks, it is possible to determine the affection of pressure field on these specifications. Stress tensor analysis is also able to determine the points in which the probability of defection creation is more. Besides, from pressure field, it is possible to analyze the affection of various fluid specifications such as viscosity and density on defect created in the material. In this research, the concerned boundary conditions are analyzed first. Then the solution network and stencil used are mentioned. With the determination of relevant equation on the fluid flow between notch and matrix and their discretion according to the governed boundary conditions, these equations can be solved. Finally, with the variation creations on fluid parameters such as density and viscosity, the affection of these variations can be determined on pressure field. In this direction, the flowchart and solution algorithm with their results as vortex and current function contours for two conditions with most applications in pressing process are introduced and discussed.

Keywords: pressing, notch, matrix, flow function, vortex

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Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

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In the description of the origin of life, there are still some open gaps, e.g., the formation of macromolecules cannot be fully explained so far. The Kauffman model proposes the existence of autocatalytic sets of macromolecules which mutually catalyze reactions leading to each other’s formation. Usually, this model is simulated in one well-stirred pot only, with a continuous inflow of small building blocks, from which larger molecules are created by a set of catalyzed ligation and cleavage reactions. This approach represents the picture of the primordial soup. However, the conditions on the early Earth must have differed geographically, leading to spatially different outcomes whether a specific reaction could be performed or not. Guided by this picture, the Kauffman model is simulated in a large number of containers in parallel, with neighboring containers being connected by diffusion. In each container, only a subset of the overall reaction set can be performed. Under specific conditions, this approach leads to a larger probability for the existence of an autocatalytic metabolism than in the original Kauffman model.

Keywords: agglomeration, autocatalytic set, differential equation, Kauffman model

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Authors: Guozhen Li, Philip Hall, Nick Miles, Tao Wu, Jie Dong

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This paper presents a Euler-Lagrange model of the water-particles multiphase flows in a Vorsyl separator where particles with different densities are separated. A series of particles with their densities ranging from 760 kg/m³ to 1380 kg/m³ were fed into the Vorsyl separator with water by means of tangential inlet. The simulation showed that the feed materials acquired centrifugal force which allows most portion of the particles with a density less than water to move to the center of the separator, enter the vortex finder and leave the separator through the bottom outlet. While the particles heavier than water move to the wall, reach the throat area and leave the separator through the side outlet. The particles were thus separated and particles collected at the bottom outlet are pure and clean. The influence of particle density on separation efficiency was investigated which demonstrated a positive correlation of the separation efficiency with increasing density difference between medium liquid and the particle. In addition, the influence of the split ratio on the performance was studied which showed that the separation efficiency of the Vorsyl separator can be improved by the increase of split ratio. The simulation also suggested that the Vorsyl separator may not function when the feeding velocity is smaller than a certain critical feeding in velocity. In addition, an increasing feeding velocity gives rise to increased pressure drop, however does not necessarily increase the separation efficiency.

Keywords: Vorsyl separator, separation efficiency, CFD, split ratio

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Authors: Kasirga Yildirak, Ismail Gur

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We propose a model to measure hail risk of an Agricultural Insurance portfolio. Hail is one of the major catastrophic event that causes big amount of loss to an insurer. Moreover, it is very hard to predict due to its strange atmospheric characteristics. We make use of parcel based claims data on apricot damage collected by the Turkish Agricultural Insurance Pool (TARSIM). As our ultimate aim is to compute the loadings assigned to specific parcels, we build a portfolio risk model that makes use of PD and the severity of the exposures. PD is computed by Spherical-Linear and Circular –Linear regression models as the data carries coordinate information and seasonality. Severity is mapped into integer brackets so that Probability Generation Function could be employed. Individual regressions are run on each clusters estimated on different criteria. Loss distribution is constructed by Panjer Recursion technique. We also show that one risk-one crop model can easily be extended to the multi risk–multi crop model by assuming conditional independency.

Keywords: hail insurance, spherical regression, circular regression, spherical clustering

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Authors: Hoda Manafian, Stephen Holland

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Problem statement: Rural areas in Iran are one of the most popular tourism destinations. Abyaneh Village is one of them with a long history behind it (more than 1500 years) which is a national heritage site and also is nominated as a world heritage site in UNESCO tentative list from 2007. There is a considerable foundation of religious-cultural heritage and also agricultural history and activities. However, this heritage site suffers from mass tourism which is beyond its social and physical carrying capacity, since the annual number of tourists exceed 500,000. While there are four adjacent villages around Abyaneh which can benefit from advantages of tourism. Local managers also can at the same time prorate the tourists’ flux of Abyaneh on those other villages especially in high-season. The other villages have some cultural and natural tourism attractions as well. Goal: The main goal of this study is to identify a feasible development strategy according to the current strengths, weaknesses, opportunities and threats of rural tourism in this area (Abyaneh Village and four adjacent villages). This development strategy can lead to sustainable management of these destinations. Method: To this end, we used SWOT analysis as a well-established tool for conducting a situational analysis to define a sustainable development strategy. The procedures included following steps: 1) Extracting variables of SWOT chart based on interviewing tourism experts (n=13), local elites (n=17) and personal observations of researcher. 2) Ranking the extracted variables from 1-5 by 13 tourism experts in Isfahan Cultural Heritage, Handcrafts and Tourism Organization (ICHTO). 3) Assigning weights to the ranked variables using Expert Choice Software and the method of Analytical Hierarchical Process (AHP). 4) Defining the Total Weighted Score (TWS) for each part of SWOT chart. 5) Identifying the strategic position according to the TWS 6) Selecting the best development strategy based on the defined position using the Strategic Position and Action Evaluation (SPACE) matrix. 7) Assessing the Probability of Strategic Success (PSS) for the preferred strategy using relevant formulas. 8) Defining two feasible alternatives for sustainable development. Results and recommendations: Cultural heritage attractions were first-ranked variable in strength chart and also lack of sufficient amenities for one-day tourists (catering, restrooms, parking, and accommodation) was firs-ranked weakness. The strategic position was in ST (Strength-Threat) quadrant which is a maxi-mini position. According this position we would suggest ‘Competitive Strategy’ as a development strategy which means relying on strengths in order to neutralization threats. The result of Probability of Strategic Success assessment which was 0.6 shows that this strategy could be successful. The preferred approach for competitive strategy could be rebranding the market of tourism in this area. Rebranding the market can be achieved by two main alternatives which are based on the current strengths and threats: 1) Defining a ‘Heritage Corridor’ from first adjacent village to Abyaneh as a final destination. 2) Focus on ‘educational tourism’ versus mass tourism and also green tourism by developing agritourism in that corridor.

Keywords: Abyaneh village, rural tourism, SWOT analysis, sustainable strategies

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Authors: Mary Holstein

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Objective: The aim of this study was to evaluate nurse leader confidence in emergency management and disaster preparedness in the state of Texas. My project was a replication study of a survey conducted in 2022 by Reedy et al, for members of the Northwest Organization for Nurse Leaders (NONL). Background: In 2022, the American Association of Colleges of Nursing (AACN) approved new essentials for academic nursing education programs to demonstrate competencies in disaster management, yet no integration of such information into nursing curriculum had been reported in the literature. Research replicated by members of the Texas Organization for Nursing Leadership suggested significant gaps in nurse leader confidence across roles and in structured education that prepares nurse leaders across the spectrum of experience to lead in a crisis. Methods: An exploratory, cross-sectional survey used a sample of 86 RNs who were members of TONL. Results: Results replicated comparable results with significant variance in nurse leader confidence across roles, experience, and previous disaster-related education. Positive associations regarding nurse leaders' confidence in managing disasters were obvious with more advanced positions, further education, and mandatory training. Conclusions: Nursing leaders in Texas lack mandatory and structured education to prepare for emergency and disaster management. The call for mandatory emergency management training and disaster preparedness for nurse leaders remains unmet.

Keywords: confidence, disaster, education, emergency

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Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

Procedia PDF Downloads 392

Authors: Lu Anne A. Godinez, May Claudine I. Gador, Preacious G. Gumolon, Louiechi Von R. Mendoza, Neil Bryan N. Moninio

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Gender equality and women empowerment is the third of eight Millennium Development Goals. Understanding corruption’s linkages to gender equality issues and how it impacts women’s empowerment is part of the broader process of advancing women’s rights and understanding the gender dimensions of democratic governance. Taking a long view of political (corruption index) and the social (women empowerment) dimension — a view from 2015 to 2030, a context based forecast was conducted to forecast the ASEAN corruption index in the next 15 years, answering the question: “Does women political involvement decrease corruption rate index of ASEAN countries in the next 15 years?” The study have established that there will be an increase women political involvement in the ASEAN countries in the next 15 years that will cause a drop on corruption rate index. There will be a significant decline on corruption rate index in 2030. This change entails reform not only in the political aspect of progress, but to the social aspect as well. Finally, the political aspect is increasing at a constant rate however a double or triple increase of the social aspect is seen to be the key solution for corruption.

Keywords: women, women political involvement, corruption, gender equity index, economic participation, educational attainment, political empowerment, control of corruption, regulatory quality, rule of law, voice and accountability government effectiveness, political stability and corruption perception index

Procedia PDF Downloads 422

Authors: Nadezhda Kvatashidze

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The International Accounting Standards Board updated the conceptual framework for financial reporting. The main reason behind it is to resolve the tasks of the accounting, which are caused by the market development and business-transactions of a new economic content. Also, the investors call for higher transparency of information and responsibility for the results in order to make a more accurate risk assessment and forecast. All these make it necessary to further develop the conceptual framework for financial reporting so that the users get useful information. The market development and certain shortcomings of the conceptual framework revealed in practice require its reconsideration and finding new solutions. Some issues and concepts, such as disclosure and supply of information, its qualitative characteristics, assessment, and measurement uncertainty had to be supplemented and perfected. The criteria of recognition of certain elements (assets and liabilities) of reporting had to be updated, too and all this is set out in the updated edition of the conceptual framework for financial reporting, a comprehensive collection of concepts underlying preparation of the financial statement. The main objective of conceptual framework revision is to improve financial reporting and development of clear concepts package. This will support International Accounting Standards Board (IASB) to set common “Approach & Reflection” for similar transactions on the basis of mutually accepted concepts. As a result, companies will be able to develop coherent accounting policies for those transactions or events that are occurred from particular deals to which no standard is used or when standard allows choice of accounting policy.

Keywords: conceptual framework, measurement basis, measurement uncertainty, neutrality, prudence, stewardship

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

Procedia PDF Downloads 299