Search results for: generalized random graphs

Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

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There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

Procedia PDF Downloads 353

Authors: Simon Ayorinde Okanlawon

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This study examines residents’ assessment of with infrastructural facilities in the urban fringe of Ibadan, Nigeria. Random sampling technique was used in selecting four Local Government Areas out of the six suburban LGAs of the city. Google earth and ground trotting were used in capturing and selecting seven hundred and forty-two new houses. The questionnaires administered on house owners were harvested on the spot. The information collected includes socio-economic and demographic characteristics of residents as well as characteristics of infrastructural facilities. The study utilised both descriptive and inferential statistical analyses; Facility Availability Index (FAI) Facility Functionality Index (FFI) and Residents’ Satisfactions Index (RSI) were used to compare respectively residents’ perceived levels of availability of, the functionality of, and satisfaction with facilities across Local Government Areas. The study shows that levels of both availability of, and satisfaction with infrastructural facilities are low with respective overall FAI (0.8) and RSI (0.05), while the functionality of the facilities is generally very poor IFFI = - 0.58). Strategies were proposed to enhance the good, livable, and healthy environment.

Keywords: infrastructural facilities, infrastructural perception index, residents’ satisfaction, urban fringe of Ibadan

Procedia PDF Downloads 223

Authors: Mehravar Javid, James Sexton, Farzaneh Amani, Kainaz Patravala

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Self-expansion is a procedure through which people expand the dimensions of their self-concept by incorporating novel content into their sense and experience of identity. Greater self-expansion predicts positive consequences for individuals and romantic relationships. The self-expansion questionnaire (SEQ) originally developed by Lewandowski & Aron (2002) assumes that self-expansion is constituted of key components from the self-expansion model. This study aimed to confirm the factor structure of SEQ and adapt the questions of the scale to the Iranian culture. The sample included 190 participants who responded to 14 items and were selected by simple random sampling. Using Amos-21 and SPSS-21, descriptive statistics, Pearson correlation and Confirmatory Factor Analysis (CFA) were calculated. Cronbach’s alpha coefficient for total SEQ items was 0.92. Results of CFA supported the factor structure SEQ [RMSEA=0.08, GFI=0.88 and CFI=0.92] that showed the model has a good fit and also all the items of SEQ, have a high correlation and have a direct and significant relationship. So, the SEQ demonstrated acceptable psychometric properties in Tehran University students. Looking forward, it would be interesting and exciting to see the implications of the scale as applied to romantic relationships.

Keywords: validity, reliability, confirmatory factor analysis, self-expansion questionnaire

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Ciaran Friel, Jerry Suls, Patrick Robles, Frank Vicari, Joan Duer-Hefele, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant response. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit Charge 4 fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7, but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by the Fitbit for two weeks. Participants then engaged with a clinical research coordinator to review comprehension of the text message content and required actions for each of the BCTs to be tested. Participants then selected a consistent daily time in which they would receive their text message prompt. In the 8 week intervention phase of the study, participants received each of the four BCTs, in random order, for a two week period. Text message prompts were delivered daily at a time selected by the participant. All prompts required an interactive response from participants and may have included recording their detailed plan for walking or daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves with peers (self-monitoring, feedback). At the end of each two week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. Analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design, and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, 5 days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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Authors: Laura Sapranaviciute-Zabazlajeva, Abdonas Tamosiunas, Dalia Luksiene, Dalia Virviciute

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The cardiovascular diseases (CVD) is the leading cause of death in the EU, especially in the middle aged and elderly population. Psychological wellbeing (PWB) has been linked with better cardiovascular health and survival in the elderly. The aim of the study is to evaluate associations between CVD risk and PWB in middle-aged and elderly population. 10,940 middle aged and older Lithuanians of age 45-74 years, were invited to participate in the study. A study sample was a random and stratified by gender and age. In 2006-2008 7,087 responders participated in the survey, so the response rate was 64.8%. A follow-up study was conducted from 2006 till 2015. New CVD cases and deaths from CVD were evaluated using the Kaunas population-based CVD register and death register of Kaunas. Study results revealed that good PWB predicts longer life in female participants (Log Rank = 13.7, p < 0.001). In the fully adjusted model for socio-demographic, social and CVD risk factors, hazard ratio for CVD mortality risk was lower amongst women with good PWB (HR = 0.28, 95% CI 0.11-0.72), but not significantly for men. Our study concludes, that lower CVD mortality rates is being associated with better PWB in female aged 45-74 years.

Keywords: psychological well-being, cardiovascular disease, elderly, survival

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Authors: Massimiliano Condotta, Paolo Ruggeri, Chiara Scanagatta, Giovanni Borga

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Architects and urban planners, when designing and renewing cities, have to face a complex set of problems, including the issues of noise and air pollution which are considered as hot topics (i.e., the Clean Air Act of London and the Soundscape definition). It is usually taken for granted that these problems go by together because the noise pollution present in cities is often linked to traffic and industries, and these produce air pollutants as well. Traffic congestion can create both noise pollution and air pollution, because NO₂ is mostly created from the oxidation of NO, and these two are notoriously produced by processes of combustion at high temperatures (i.e., car engines or thermal power stations). We can see the same process for industrial plants as well. What have to be investigated – and is the topic of this paper – is whether or not there really is a correlation between noise pollution and air pollution (taking into account NO₂) in urban areas. To evaluate if there is a correlation, some low-cost methodologies will be used. For noise measurements, the OpeNoise App will be installed on an Android phone. The smartphone will be positioned inside a waterproof box, to stay outdoor, with an external battery to allow it to collect data continuously. The box will have a small hole to install an external microphone, connected to the smartphone, which will be calibrated to collect the most accurate data. For air, pollution measurements will be used the AirMonitor device, an Arduino board to which the sensors, and all the other components, are plugged. After assembling the sensors, they will be coupled (one noise and one air sensor) and placed in different critical locations in the area of Mestre (Venice) to map the existing situation. The sensors will collect data for a fixed period of time to have an input for both week and weekend days, in this way it will be possible to see the changes of the situation during the week. The novelty is that data will be compared to check if there is a correlation between the two pollutants using graphs that should show the percentage of pollution instead of the values obtained with the sensors. To do so, the data will be converted to fit on a scale that goes up to 100% and will be shown thru a mapping of the measurement using GIS methods. Another relevant aspect is that this comparison can help to choose which are the right mitigation solutions to be applied in the area of the analysis because it will make it possible to solve both the noise and the air pollution problem making only one intervention. The mitigation solutions must consider not only the health aspect but also how to create a more livable space for citizens. The paper will describe in detail the methodology and the technical solution adopted for the realization of the sensors, the data collection, noise and pollution mapping and analysis.

Keywords: air quality, data analysis, data collection, NO₂, noise mapping, noise pollution, particulate matter

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: Joshua Abraham, Craig Wales

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Abstract—SIGN Guideline 122 recommends that all patients who are admitted to hospital are assessed for venous thromboembolism risk within 24 hours of admission. NHS Greater Glasgow and Clyde provide guidance on this in the form of a proforma. Patients are then subsequently prescribed either thrombo-embolic-deterrent stockings (TEDS)/low molecular weight heparin (LMWH) for the prevention of VTE based on their score. A retrospective casenote audit of a random sample of fifty oncology and trauma inpatients at the QEUH in December 2019 was performed. 90% of patients had a risk assessment conducted as evidenced by a completed proforma. In 78% of these patients, the proforma fully completed. Overall 94% of patients had some for of thromboprophylaxis prescribed in the form of TEDS or LMWH. A lack of 100% compliance against the given standards highlighted potential implications for patient safety, but also medico-legal ramifications for staff. Clinical judgement can only be relied upon if there is written documentation as evidence. Further staff education and the suggestion of a written prompt to the clerk-in documentation will hopefully improve compliance, whilst a repeat audit should demonstrate any improvement.

Keywords: Maxillofacial , Thromboembolism, Thromboprophylaxis , Prescription

Procedia PDF Downloads 159

Authors: Yuri Teraoka, Cheerawit Rattanapan, Aroonsri Mongkolchati

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This cross sectional analytic study was carried out to determine factors related to protective behavior on indoor pollution among pregnant women in Nakhon Pathom province, Thailand. A total of 319 pregnant women were enrolled at three antenatal care clinics in community hospital. Data were collected using simple random sampling from April 2015 to May 2015 using a structured self-administration questionnaire by well-trained research assistants. The result showed that around 73% pregnant women showed low level of low protective behavior on indoor pollution. Chi-square and multiple logistic regression were used to examine the factors and protective behavior on indoor pollution. After adjusting for confounding factors, this study found that tobacco smoking before pregnancy (AOR=2.15, 95% CI: 0.78-5.95) and low environmental health hazard (AOR=1.94, 95% CI: 1.09-3.49) were significant factors related to protective behavior on indoor pollution among pregnant women (p-value < 0.05). In conclusion, this study suggested that environmental health education campaign and environmental implementation program among pregnant woman are needed.

Keywords: Thailand, environmental health, protective behavior, pregnant women

Procedia PDF Downloads 364

Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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Authors: Dewi Fatmaningrum, Ade Wiradnyani

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Background: Optimal feeding, include optimal micronutrient intake, becomes one of the ways to overcome the long-term consequences of undernutrition. Macronutrient and micronutrient intake were important for rapid growth and development of the children. Objectives: To assess macro and micronutrient intake of children aged 12-23 months old and nutrients inadequacy from intake of children aged 12-23 months old. Methods: This survey was a cross-sectional study, simple random sampling was performed to select respondents. Total sample of this study was 83 children aged 12-23 months old in Paseban Village, Senen Sub-district, Central Jakarta. The data was collected via interview and hemoglobin measurement of children. Results: The highest prevalence of inadequacy was iron intake (52.4%) compared to other micronutrients, 11.98% children had inadequate energy intake. There were 62.6% anemic children in the study area in which divided into anemic (37.3%) and severe anemic (25.3%). Conclusion: Micronutrient inadequacy occurred more frequently than macronutrient inadequacy in the study area. The higher the percentage of iron inadequacy gets, the higher the percentage of anemia among children is observed.

Keywords: micronutrient, macronutrient, children under five, urban setting

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Authors: E. Rahimi, S. Shaigannia

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Salmonella typhimurium and Salmonella enteritidis are important infectious agents causing food poisoning and food-borne gastrointestinal diseases. This study was carried out in order to investigate the distribution of virulence genes and antimicrobial resistance properties of S. typhimurium and S. enteritidis isolated from ruminant milk and dairy products in Iran. Overall 360 raw and pasteurized milk and traditional and commercial dairy products were purchased from random selected supermarkets and retail stories of Isfahan province, Iran. Samples were cultured immediately and those found positive for Salmonella were analyzed for the presence of S. typhimurium, S. enteritidis and several putative genes using PCR. Totally, 13 (3.61%), 8 (2.22%), 1 (0.27%) and 4 (1.11%) samples were found to be contaminated with Salmonella spp., S. typhimurium, S. enteritidis and other species of Salmonella, respectively. PCR results showed that invA, rfbJ, fliC and spv were the detected virulence genes in S. typhimurium and S. enteritidis positive samples. To the authors’ knowledge, the present study is the first prevalence report of virulence genes of S. typhimurium and S. enteritidis isolated from ruminant milk and traditional and commercial dairy products in Iran.

Keywords: Salmonella typhimurium, Salmonella enteritidis, virulence genes, ruminant milk, dairy products

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Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

Procedia PDF Downloads 467

Authors: Tahsien Mohamed Okasha

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Simulation is one of the emerging educational strategies that depend on the creation of scenarios to imitate what could happen in real life. At the time of COVID, we faced big obstacles in medical education, specially the clinical part and how we could apply it, the simulation was the golden key. Simulation is a very important tool of education for medical sector students, through creating a safe, changeable, quiet environment with less anxiety level for students to practice and to have repeated trials on their competencies. That impacts the level of practice, achievement, and the way of acting in real situations and experiences. A blind Random sample of students from different specialties and colleges who came and finished their training in an integrated environment was collected and tested, and the responses were graded from (1-5). The results revealed that 77% of the studied subjects agreed that dealing and interacting with different medical sector candidates in the same place was beneficial. 77% of the studied subjects agreed that simulations were challenging in thinking and decision-making skills .75% agreed that using high-fidelity manikins was helpful. 75% agree .76% agreed that working in a safe, prepared environment is helpful for realistic situations.

Keywords: simulation, clinical training, education, medical sector students

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Authors: Avinash Malladhi

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Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

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Authors: Hafiza Khaddija Saman, Muhammad Sufyan

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The increase in availability and popularity of mobile wireless devices has led researchers to develop a wide variety of Mobile Ad-hoc Networking (MANET) protocols to exploit the unique communication opportunities presented by these devices. Devices are able to communicate directly using the wireless spectrum in a peer-to-peer fashion, and route messages through intermediate nodes, however, the nature of wireless shared communication and mobile devices result in many routing and security challenges which must be addressed before deploying a MANET. In this paper, we investigate the range of MANET routing protocols available and discuss the functionalities of several ranging from early protocols such as DSDV to more advanced such as MAODV, our protocol study focuses upon works by Perkins in developing and improving MANET routing. A range of literature relating to the field of MANET routing was identified and reviewed, we also reviewed literature on the topic of securing AODV based MANETs as this may be the most popular MANET protocol. The literature review identified a number of trends within research papers such as exclusive use of the random waypoint mobility model, excluding key metrics from simulation results and not comparing protocol performance against available alternatives.

Keywords: protocol, MANET, ad-Hoc, communication

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Jailan Mohamed El Demerdash

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In consideration of the challenges and the fierce global competition that have emerged in today’s hotel industry, it was important to shed light on the subject of strategic management. In addition, five-star hotels play a crucial role in supporting the tourism industry and investment in Egypt. Therefore, this study aims at exploring the scope of implementing strategic management practices in five-star hotels in Egypt and examining the differences between resorts and downtown hotels regarding the implementation of a strategic management process. The impact of the difference in hotel types on the implementation of the strategic management process will be examined. Simple random sampling technique will be employed to select the sample from the target population, including hotels from Sharm El- Sheikh, Cairo, and Hurghada cities. The data collection instrument employed in the current study is an interviewer-administered questionnaire. Eventually, combining the results of the study with the literature review helped to present a number of recommendations that have to be directed to hotel managers in the area of strategic management practices.

Keywords: strategic management, strategic tools, five-star hotels, resorts, downtown hotels, Egypt

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Authors: Chun-Qing Li, Hassan Baji, Wei Yang

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Corrosion of steel in reinforced concrete structures is a major problem worldwide. The volume expansion of corrosion products causes concrete cover cracking, which could lead to delamination of concrete cover. The time to cover cracking plays a key role to the assessment of serviceability of reinforced concrete structures subjected to corrosion. Many analytical, numerical, and empirical models have been developed to predict the time to cracking initiation due to corrosion. In this study, a numerical model based on finite element modeling of corrosion-induced cracking process is used. In order to predict the service life based on time to cover initiation, the numerical approach is coupled with a probabilistic procedure. In this procedure, all the influential factors affecting time to cover cracking are modeled as random variables. The results show that the time to cover cracking is highly variables. It is also shown that rust product expansion ratio and the size of more porous concrete zone around the rebar are the most influential factors in predicting service life of corrosion-affected structures.

Keywords: corrosion, crack width, probabilistic, service life

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Authors: Ala Rakhshandeh, Zahra Ashkar, Solmaz Dehghani Dolatabadi, Hossein Bayat

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The present study has been conducted to investigate the role of family emotional climate and emotional expression style in the academic well-being of students with military parents. Children, including 280 female students of Shahriar police officers, were selected by random sampling method, and they have been investigated through Alfred B. Hillburn's family emotional climate questionnaire (1964), King and Ammon's emotional expression questionnaire (1990), and Pitrinen, Sweeney, and Falto's academic well-being questionnaire (2014). The data were analyzed using statistical methods of correlation coefficient and stepwise multiple regression under the SPSS23 program. The results reveal that the variables of family emotional climate and emotional expression can explain 36.4% of the variance in academic well-being. This finding reveals that with an increase of standard deviation on the scores of family emotional climate and emotional expression, 0.513 and 0.155 standard deviations are added to the scores of academic well-being, respectively. The emotional climate of the family has a superior distinctive role in predicting the educational well-being of female students. Thus, the emotional climate of the family and the style of emotional expression play a meaningful role in the academic well-being of students with the military parent.

Keywords: emotional climate, family, emotional expression style, academic well-being

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Authors: Jong Yeop Kim, Sung Young Park, Dae Hee Kim, Han Bum Joe, Ji Young Yoo, Jong Bum Choi, Sook Young Lee

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Emergence agitation (EA) is commonly reported adverse events after sevoflurane anesthesia in pediatric patients. The efficacy of prophylactic remifentanil, one of mu opioid agonist, in preventing EA is controversial. This meta-analysis assessed the effectiveness of remifentanil to decrease the incidence of EA from sevoflurane anesthesia in children. We searched for randomized controlled trials comparing sevoflurane alone anesthesia with sevoflurane and remifentanil anesthesia to prevent EA in the Cochrane Library, Embase, Pubmed, and KoreaMed, and included 6 studies with 361 patients. The number of patients of reporting EA was summarized using risk ratio (RR) with 95% confidence interval (CI), with point estimates and 95CIs derived from a random effects Mantel-Haenszel method. Overall incidence of EA was about 41%. Compared with sevoflurane alone anesthesia, intravenous infusion of remifentanil with sevoflurane significantly reduced the incidence of EA (RR 0.53, 95% CI 0.39-0.73, P < 0.0001), (heterogeneity, I2 = 0, P = 0.42). This meta-analysis suggested that continuous infusion of remifentanil could be effective in decreasing the EA of about 47% after sevoflurane anesthesia. However, considering limitations of the included studies, more randomized controlled studies are required to verify our results.

Keywords: emergence agitation, meta-analysis, remifentanil, pediatrics

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Authors: Celestina Omoso Isiramen

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The influence of witchcraft belief on disease causation, cure and public health system in Nigeria cannot be underrated. This paper investigated the nexus between witchcraft phenomenon and health-seeking behaviour of HIV sufferers in Edo state, Nigeria. Survey methodology was adopted and stratified random sampling technique was employed in the selection of 600 sample group spread into 200 HIV sufferers, 200 spiritual healers and 200 bio-medics from the three Senatorial districts of the state. Data were collected through the use of structured questionnaire and in-dept interview and analyzed using simple percentage and frequency. Major findings were: belief in witchcraft significantly influenced the people’s perception of HIV causation and wellness and this impacted adversely on public health-care. Poverty, ignorance and dearth of retroviral drugs enhanced the people’s recourse to spiritual healers. Collaboration between spiritual healing techniques and biomedicine was recommended as panacea for curbing HIV/AIDS related morbidity and mortality. It concluded that socio-economic problems must be addressed while the importance of integrating the values of spiritual healing into biomedicine cannot be overstressed.

Keywords: biomedicine, health care, HIV/AIDS, spirituality, witchcraft

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Authors: Jana Aleksić, Marijana Petković

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Female population has an increasing role when it comes to purchase. Consequently, the female population has a greater role in modern marketing. Although it is thought that women buy more than men, marketing strategy was not directed specifically towards women. The thing that has changed regarding women’s role in modern marketing is the fact that the female population has a leading position when it comes to decision making in various fields and various sectors, which was not the case in the past. Marketing should be directed towards women but it should be done in the right way. Compared to men, women buy in a different way, and they look for more various advantages in the product itself, than men do. This paper aims to show the importance of the female role in the modern marketing and management and to redirect marketing in some way towards female population through new marketing strategies and management systems. Hypothesis is that women have an important role in marketing, and marketing strategy of modern society could and should be based on and directed towards female population and their tastes when it comes to purchasing. It is necessary and desirable to apply marketing strategy with a special strategy that has an emphasis on women and their purchase or in a word to apply WS- woman strategy. This research was carried out as a random sample research, where were obtained 212 valid surveys whose results serve as a basis for drawing conclusions about the research as well as to verify the formulated hypotheses. The research was carried out during 2011 and 2012. The study has shown a significant role of the female population in the marketing process.

Keywords: marketing, management, female, purchase, strategy

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Authors: Juyeon Lee, Sungeun You

Abstract:

Experiential avoidance is one’s tendency to avoid painful internal experience, unwanted adverse thoughts, emotions, and physical sensations. The Multidimensional Experiential Avoidance Questionnaire (MEAQ) is a measure of experiential avoidance, and the original scale consisted of 62 items with six subfactors including behavioral avoidance, distress aversion, procrastination, distraction/suppression, repression/denial, and distress endurance. The purpose of this study was to examine the factor structure of the MEAQ in a Korean sample. Three hundred community adults and university students aged 18 to 35 participated in an online survey assessing experiential avoidance (MEAQ and Acceptance and Action Questionnaire-II; AAQ-II), depression (Patient Health Questionnaire-9; PHQ-9), anxiety (Generalized Anxiety Disoder-7; GAD-7), negative affect (Positive and Negative Affect Scale; PANAS), neuroticism (Big Five Inventory; BFI), and quality of life (Satisfaction with Life Scale; SWLS). Factor analysis with principal axis with direct oblimin rotation was conducted to examine subfactors of the MEAQ. Results indicated that the six-factor structure of the original scale was adequate. Eight items out of 62 items were removed due to insufficient factor loading. These items included 3 items of behavior avoidance (e.g., “When I am hurting, I would do anything to feel better”), 2 items of repression/denial (e.g., “I work hard to keep out upsetting feelings”), and 3 items of distress aversion (e.g., “I prefer to stick to what I am comfortable with, rather than try new activities”). The MEAQ was positively associated with the AAQ-II (r = .47, p < .001), PHQ-9 (r = .37, p < .001), GAD-7 (r = .34, p < .001), PANAS (r = .35, p < .001), and neuroticism (r = .24, p < .001), and negatively correlated with the SWLS (r = -.38, p < .001). Internal consistency was good for the MEAQ total (Cronbach’s α = .90) as well as all six subfactors (Cronbach’s α = .83 to .87). The findings of the study support the multidimensional feature of experiential avoidance and validity of the MEAQ in a sample of Korean adults.

Keywords: avoidance, experiential avoidance, factor structure, MEAQ

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Authors: Vural Erdogan

Abstract:

We created two-dimensional hexagonal cellular automata to obtain complexity by using simple rules same as Conway’s game of life. Considering the game of life rules, Wolfram's works about life-like structures and John von Neumann's self-replication, self-maintenance, self-reproduction problems, we developed 2-states and 3-states hexagonal growing algorithms that reach large populations through random initial states. Unlike the game of life, we used six neighbourhoods cellular automata instead of eight or four neighbourhoods. First simulations explained that whether we are able to obtain sort of oscillators, blinkers, and gliders. Inspired by Wolfram's 1D cellular automata complexity and life-like structures, we simulated 2D synchronous, discrete, deterministic cellular automata to reach life-like forms with 2-states cells. The life-like formations and the oscillators have been explained how they contribute to initiating self-maintenance together with self-reproduction and self-replication. After comparing simulation results, we decided to develop the algorithm for another step. Appending a new state to the same algorithm, which we used for reaching life-like structures, led us to experiment new branching and fractal forms. All these studies tried to demonstrate that complex life forms might come from uncomplicated rules.

Keywords: hexagonal cellular automata, self-replication, self-reproduction, self- maintenance

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Authors: Oscar Javier Herrera, Manuel Angel Camacho

Abstract:

This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors’. The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: demand forecasting, empirical distribution, propagation of error, Bogota

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

Abstract:

The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

Procedia PDF Downloads 182