Search results for: Cox regression model

Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: information overload, computers, mobile devices, digital media, information literacy, students

Procedia PDF Downloads 271

Authors: Elham Jelodari Mamaghani, Christian Prins, Haoxun Chen

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In this paper, there is concentration on collaborative transportation planning (CTP) among multiple carriers with pickup and delivery requests and time windows. This problem is a vehicle routing problem with constraints from standard vehicle routing problems and new constraints from a real-world application. In the problem, each carrier has a finite number of vehicles, and each request is a pickup and delivery request with time window. Moreover, each carrier has reserved requests, which must be served by itself, whereas its exchangeable requests can be outsourced to and served by other carriers. This collaboration among carriers can help them to reduce total transportation costs. A mixed integer programming model is proposed to the problem. To solve the model, a hybrid algorithm that combines Genetic Algorithm and Simulated Annealing (GASA) is proposed. This algorithm takes advantages of GASA at the same time. After tuning the parameters of the algorithm with the Taguchi method, the experiments are conducted and experimental results are provided for the hybrid algorithm. The results are compared with those obtained by a commercial solver. The comparison indicates that the GASA significantly outperforms the commercial solver.

Keywords: centralized collaborative transportation, collaborative transportation with pickup and delivery, collaborative transportation with time windows, hybrid algorithm of GA and SA

Procedia PDF Downloads 386

Authors: Imren Kutlu, Nurdilek Gulmezoglu

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Triticale (Triticosecale Wittmack) is a man-made crop developed by crossing wheat (Triticum L.) and rye (Secale cereale L.). Triticale has until now been used mostly for animal feed; however, it can be consumed by humans in the form of biscuits, cookies, and unleavened bread. Moreover, one of the reasons for the development of triticale is that it is more efficient in nutrient deficient soil than wheat cultivars. After nitrogen fertilizer, phosphorus (P) is the most used fertilizer for crop production because P fixation occurs highly when it is applied the soil. The aim of the present study was to evaluate P uptake of winter triticale genotypes under different P fertilizer rates in different growth stages. The experiment was conducted in Eskisehir, Central Anatolia, Turkey. Treatments consisted of five triticale lines and one triticale cultivars (Samursortu) with four rates of P fertilization (0, 30, 60 and 120 kg P2O5 ha⁻¹). Phosphorus uptake of triticale genotypes in tillering, heading, as well as grain and straw at harvest stage and yield of grain and straw were determined. The results showed that a P rate of 60 kg/ha and the TCL-25 genotype produced the highest yields of straw and grain at harvest. Phosphorus uptake was the highest in tillering stage, and it decreased towards to harvest time. Phosphorus uptake of all growth stage increased as P rates raised and the application of 120 kg/ha P₂O₅ had the highest P uptake. Phosphorus uptake of genotypes was found differently. The regression analyses indicated that P uptake at tillering stage was the most effective on grain yield. These results will provide useful information to triticale growers about suitable phosphorus fertilization for both forage and food usage.

Keywords: grain yield, growth stage, phosphorus fertilization, phosphorus uptake, triticale

Procedia PDF Downloads 142

Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

Procedia PDF Downloads 146

Authors: J. R. Dinsmore, R. W. Hood

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Experiences of a divine or mystical light are frequently reported in religious/spiritual experiences today, most notably in the context of mystical and near-death experiences. Light of a transcendental nature and its experiences of it are also widely present and highly valued in many religious and mystical traditions. Despite the significance of this luminosity to the topic of religious experience, efforts to study the phenomenon empirically have been minimal and scattered. This mixed methods study developed and validated a questionnaire for the measurement of numinous luminosity experience and investigated the dimensions and effects of this novel construct using both quantitative and qualitative methodologies. A sequential explanatory design (participant selection model) was used, which involved a scale development phase, followed by a correlational study testing hypotheses about its effects on beliefs and well-being derived from the literature, and lastly, a phenomenological study of a sample selected from the correlational phase results. The outcomes of the study are a unified theoretical model of numinous luminosity experience across multiple experiential contexts, initial correlational findings regarding the possible mechanism of its reported positive transformational effects, and a valid and reliable instrument for its further empirical study.

Keywords: religious experience, mystical experience, near-death experience, scale development, questionnaire, divine light, mystical light, mystical luminosity

Procedia PDF Downloads 93

Authors: Lin Lu, Qiang Li, Tao Cai, Pengjun Zhang

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In this study, a detailed analysis of trajectory stability and flow characteristics of a high-speed projectile during the water-entry and water-exit process has been investigated numerically. The Zwart-Gerber-Belamri (Z-G-B) cavitation model and the SST k-ω turbulence model based on the Reynolds Averaged Navier-Stokes (RANS) method are employed. The numerical methodology is validated by comparing the experimental photograph of cavitation shape and the experimental underwater velocity with the numerical simulation results. Based on the numerical methodology, the influences of rotational speed, water-entry and water-exit angle of the projectile on the trajectory stability and flow characteristics have been carried out in detail. The variation features of projectile trajectory and total resistance have been conducted, respectively. In addition, the cavitation characteristics of water-entry and water-exit have been presented and analyzed. Results show that it may not be applicable for the water-entry and water-exit to achieve the projectile stability through the rotation of projectile. Furthermore, there ought to be a critical water-entry angle for the water-entry stability of practical projectile. The impact of water-exit angle on the trajectory stability and cavity phenomenon is not as remarkable as that of the water-entry angle.

Keywords: cavitation characteristics, high-speed projectile, numerical predictions, trajectory stability, water-entry, water-exit

Procedia PDF Downloads 132

Authors: Fred N. H. Parker, Nicola T. Fear, S. A. M. Stevelink, L. Rafferty

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Purpose Auditory problems, such as hearing loss and tinnitus, have been associated with mental health problems and alcohol misuse in the UK general population and in the US Armed Forces; however, few studies have examined these associations within the UK Armed Forces. The present study examined the association between auditory problems and probable common mental disorders, post-traumatic stress disorder and alcohol misuse. Methods 5474 serving and ex-service personnel from the UK Armed Forces were examined, selected from those who responded to phase two (data collection 2007–09) and phase three (2014–16) of a military cohort study. Multivariable logistic regression was used to examine the association between auditory problems at phase two and mental health problems at phase three. Results 9.7% of participants reported ever experiencing hearing problems alone, 7.9% reported tinnitus within the last month alone, and 7.8% reported hearing problems with tinnitus. After adjustment, hearing problems with tinnitus at phase two was associated with increased odds of probable common mental disorders (AOR = 1.50, 95% CI 1.09–2.08), post-traumatic stress disorder (AOR = 2.30, 95% CI 1.41–3.76), and alcohol misuse (AOR = 1.94, 95% CI 1.28–2.96) at phase three. Tinnitus alone was associated with probable post-traumatic stress disorder (AOR = 1.80, 95% CI 1.03–3.15); however, hearing problems alone were not associated with any outcomes of interest. Conclusions The association between auditory problems and mental health problems emphasizes the importance of the prevention of auditory problems in the Armed Forces: through enhanced audiometric screening, improved hearing protection equipment, and greater levels of utilization of such equipment.

Keywords: armed forces, hearing problems, tinnitus, mental health, alcohol misuse

Procedia PDF Downloads 162

Authors: Ayesha Akbar

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Public service delivery has witnessed a significant improvement with the integration of information communication technology (ICT). It not only improves management structure with advanced technology for surveillance of service delivery but also provides evidence for informed decisions and policy. Pakistan’s public sector organizations have not been able to produce some good results to ensure service delivery. Notwithstanding, some of the public sector organizations in Pakistan has diffused modern technology and proved their credence by providing better service delivery standards. These good indicators provide sound basis to integrate technology in public sector organizations and shift of policy towards evidence based policy making. Rescue-1122 is a public sector organization which provides emergency services and proved to be a successful model for the provision of service delivery to save human lives and to ensure human development in Pakistan. The information about the organization has been received by employing qualitative research methodology. The information is broadly based on primary and secondary sources which includes Rescue-1122 website, official reports of organizations; UNDP (United Nation Development Program), WHO (World Health Organization) and by conducting 10 in-depth interviews with the high administrative staff of organizations who work in the Lahore offices. The information received has been incorporated with the study for the better understanding of the organization and their management procedures. Rescue-1122 represents a successful model in delivering the services in an efficient way to deal with the disaster management. The management of Rescue has strategized the policies and procedures in such a way to develop a comprehensive model with the integration of technology. This model provides efficient service delivery as well as maintains the standards of the organization. The service delivery model of rescue-1122 works on two fronts; front-office interface and the back-office interface. Back-office defines the procedures of operations and assures the compliance of the staff whereas, front-office equipped with the latest technology and good infrastructure handles the emergency calls. Both ends are integrated with satellite based vehicle tracking, wireless system, fleet monitoring system and IP camera which monitors every move of the staff to provide better services and to pinpoint the distortions in the services. The standard time of reaching to the emergency spot is 7 minutes, and during entertaining the case; driver‘s behavior, traffic volume and the technical assistance being provided to the emergency case is being monitored by front-office. Then the whole information get uploaded to the main dashboard of Lahore headquarter from the provincial offices. The latest technology is being materialized by Rescue-1122 for delivering the efficient services, investigating the flaws; if found, and to develop data to make informed decision making. The other public sector organizations of Pakistan can also develop such models to integrate technology for improving service delivery and to develop evidence for informed decisions and policy making.

Keywords: data, e-governance, evidence, policy

Procedia PDF Downloads 243

Authors: Hary Aprianto Wijaya Siahaan, Bayu Edo Pratama

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Sea fishery's potential to become one of the nation's assets which very contributed to Indonesia's economy. This fishery potential not in spite of the availability of the chlorophyll in the territorial waters of Indonesia. The research was conducted using three methods, namely: statistics, comparative and analytical. The data used include MODIS sea temperature data imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, MODIS data of chlorophyll-a imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, and Imaging results data ASCAT on MetOp and NOAA satellites with 27 km resolution in 2002-2015. The results of the processing of the data show that the incidence of upwelling in the south of East Java Sea began to happen in June identified with sea surface temperature anomaly below normal, the mass of the air that moves from the East to the West, and chlorophyll-a concentrations are high. In July the region upwelling events are increasingly expanding towards the West and reached its peak in August. Chlorophyll-a concentration prediction using multiple linear regression equations demonstrate excellent results to chlorophyll-a concentrations prediction in 2002 until 2015 with the correlation of predicted chlorophyll-a concentration indicate a value of 0.8 and 0.3 with RMSE value. On the chlorophyll-a concentration prediction in 2016 indicate good results despite a decline in the value of the correlation, where the correlation of predicted chlorophyll-a concentration in the year 2016 indicate a value 0.6, but showed improvement in RMSE values with 0.2.

Keywords: satellite, sea surface temperature, upwelling, wind stress

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Authors: Armin Rahimi

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The Gravity Recovery and Climate Experiment (GRACE) has been a very successful project in determining math redistribution within the Earth system. Large deformations caused by earthquakes are in the high frequency band. Unfortunately, GRACE is only capable to provide reliable estimate at the low-to-medium frequency band for the gravitational changes. In this study, we computed the gravity changes after the 2012 Mw8.6 Indian Ocean earthquake off-Sumatra using the GRACE Level-2 monthly spherical harmonic (SH) solutions released by the University of Texas Center for Space Research (UTCSR). Moreover, we calculated gravity changes using different fault models derived from teleseismic data. The model predictions showed non-negligible discrepancies in gravity changes. However, after removing high-frequency signals, using Gaussian filtering 350 km commensurable GRACE spatial resolution, the discrepancies vanished, and the spatial patterns of total gravity changes predicted from all slip models became similar at the spatial resolution attainable by GRACE observations, and predicted-gravity changes were consistent with the GRACE-detected gravity changes. Nevertheless, the fault models, in which give different slip amplitudes, proportionally lead to different amplitude in the predicted gravity changes.

Keywords: undersea earthquake, GRACE observation, gravity change, dislocation model, slip distribution

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Authors: Chao-xun Liu, Shi-hong Lu

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In spite of its importance to the aerospace and automobile industries, little or no attention has been devoted to the accurate modeling of the ultrasonic shot peening (USP) process. It is therefore the purpose of this study to conduct finite element analysis of the process using a realistic multiple pin impacts model with the explicit solver of ABAQUS. In this paper, we research the effect of several key parameters on the residual stress distribution within the target, including impact velocity, incident angle, friction coefficient between pins and target and impact number of times were investigated. The results reveal that the impact velocity and impact number of times have obvious effect and impacting vertically could produce the most perfect residual stress distribution. Then we compare the results with the date in USP experiment and verify the exactness of the model. The analysis of the multiple pin impacts date reveal the relationships between peening process parameters and peening quality, which are useful for identifying the parameters which need to be controlled and regulated in order to produce a more beneficial compressive residual stress distribution within the target.

Keywords: ultrasonic shot peening, finite element, multiple pins, residual stress, numerical simulation

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Authors: H. Hruschka

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This paper presents the first comparison of the performance of the restricted Boltzmann machine and the deep belief net on binary market basket data relative to binary factor analysis and the two best-known topic models, namely Dirichlet allocation and the correlated topic model. This comparison shows that the restricted Boltzmann machine and the deep belief net are superior to both binary factor analysis and topic models. Managerial implications that differ between the investigated models are treated as well. The restricted Boltzmann machine is defined as joint Boltzmann distribution of hidden variables and observed variables (purchases). It comprises one layer of observed variables and one layer of hidden variables. Note that variables of the same layer are not connected. The comparison also includes deep belief nets with three layers. The first layer is a restricted Boltzmann machine based on category purchases. Hidden variables of the first layer are used as input variables by the second-layer restricted Boltzmann machine which then generates second-layer hidden variables. Finally, in the third layer hidden variables are related to purchases. A public data set is analyzed which contains one month of real-world point-of-sale transactions in a typical local grocery outlet. It consists of 9,835 market baskets referring to 169 product categories. This data set is randomly split into two halves. One half is used for estimation, the other serves as holdout data. Each model is evaluated by the log likelihood for the holdout data. Performance of the topic models is disappointing as the holdout log likelihood of the correlated topic model – which is better than Dirichlet allocation - is lower by more than 25,000 compared to the best binary factor analysis model. On the other hand, binary factor analysis on its own is clearly surpassed by both the restricted Boltzmann machine and the deep belief net whose holdout log likelihoods are higher by more than 23,000. Overall, the deep belief net performs best. We also interpret hidden variables discovered by binary factor analysis, the restricted Boltzmann machine and the deep belief net. Hidden variables characterized by the product categories to which they are related differ strongly between these three models. To derive managerial implications we assess the effect of promoting each category on total basket size, i.e., the number of purchased product categories, due to each category's interdependence with all the other categories. The investigated models lead to very different implications as they disagree about which categories are associated with higher basket size increases due to a promotion. Of course, recommendations based on better performing models should be preferred. The impressive performance advantages of the restricted Boltzmann machine and the deep belief net suggest continuing research by appropriate extensions. To include predictors, especially marketing variables such as price, seems to be an obvious next step. It might also be feasible to take a more detailed perspective by considering purchases of brands instead of purchases of product categories.

Keywords: binary factor analysis, deep belief net, market basket analysis, restricted Boltzmann machine, topic models

Procedia PDF Downloads 194

Authors: Freddy Patricio Moncayo-Matute, Pablo Gerardo Peña-Tapia, Vázquez-Silva Efrén, Paúl Bolívar Torres-Jara, Diana Patricia Moya-Loaiza, Gabriela Abad-Farfán

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This study describes a clinical case and the results on the application of additive manufacturing for the surgical planning in the removal of a cranial spheno-orbital meningioma. It is verified that the use of personalized anatomical models and cutting guides helps to manage the cranial anomalies approach. The application of additive manufacturing technology: Fused Deposition Modeling (FDM), as a low-cost alternative, enables the printing of the test anatomical model, which in turn favors the reduction of surgery time, as well the morbidity rate reduction too. And the printing of the personalized cutting guide, which constitutes a valuable aid to the surgeon in terms of improving the intervention precision and reducing the invasive effect during the craniotomy. As part of the results, post-surgical follow-up is included as an instrument to verify the patient's recovery and the validity of the procedure.

Keywords: surgical planning, additive manufacturing, rapid prototyping, fused deposition modeling, custom anatomical model

Procedia PDF Downloads 90

Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

Procedia PDF Downloads 41

Authors: Karim Hajjar, Luis Lillo, Diego Martinez, Manuel Hermosilla, Nicholas Risko

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Objectives: This study examines the relationship between universal health coverage (UCH) and the burden of emergency diseases at a global level. Methods: Data on Disability-Adjusted Life Years (DALYs) from emergency conditions were extracted from the Institute for Health Metrics and Evaluation (IHME) database for the years 2015 and 2019. Data on UHC, measured using two variables, 1) coverage of essential health services and 2) proportion of population spending more than 10% of household income on out-of-pocket health care expenditure, was extracted from the World Bank Database for years preceding our outcome of interest. Linear regression was performed, analyzing the effect of the UHC variables on the DALYs of emergency diseases, controlling for other variables. Results: A total of 133 countries were included. 44.4% of the analyzed countries had coverage of essential health services index of at least 70/100, and 35.3% had at least 10% of their population spend greater than 10% of their household income on healthcare. For every point increase in the coverage of essential health services index, there was a 13-point reduction in DALYs of emergency medical diseases (95% CI -16, -11). Conversely, for every percent decrease in the population with large household expenditure on healthcare, there was a 0.48 increase in DALYs of emergency medical diseases (95% CI -5.6, 4.7). Conclusions: After adjusting for multiple variables, an increase in coverage of essential health services was significantly associated with improvement in DALYs for emergency conditions. There was, however, no association between catastrophic health expenditure and DALYs.

Keywords: emergency medicine, universal healthcare, global health, health economics

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Authors: Alirıza Kaleli, M. Akif Ceviz, Erdoğan Güner, Köksal Erentürk

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The cyclic variations in spark ignition engines occurring especially under specific engine operating conditions make the maximum pressure variable for successive in-cylinder pressure cycles. Minimization of cyclic variations has a great importance in effectively operating near to lean limit, or at low speed and load. The cyclic variations may reduce the power output of the engine, lead to operational instabilities, and result in undesirable engine vibrations and noise. In this study, spark timing is controlled in order to reduce the cyclic variations in spark ignition engines. Firstly, an ARMAX model has developed between spark timing and maximum pressure using system identification techniques. By using this model, the maximum pressure of the next cycle has been predicted. Then, self-tuning minimum variance controller has been designed to change the spark timing for consecutive cycles of the first cylinder of test engine to regulate the in-cylinder maximum pressure. The performance of the proposed controller is illustrated in real time and experimental results show that the controller has a reliable effect on cycle to cycle variations of maximum cylinder pressure when the engine works under low speed conditions.

Keywords: cyclic variations, cylinder pressure, SI engines, self tuning controller

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Authors: Anuradha Maharaj, Adrian Cashman

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The cross-cutting nature of water as a resource translates into the need for a better understanding of its movement, storage and loss at all points in the hydro-socioeconomic cycle. An integrated approach to addressing the issue of sustainability means quantitatively understanding: the linkages within this cycle, the role of water managers in resource allocation, and the critical factors influencing its scarcity. The Water Evaluation and Planning Tool (WEAP) is an integrative model that combines the catchment-scale hydrologic processes with a water management model, driven by environmental requirements and socioeconomic demands. The concept of demand priorities is included to represent the areas of greatest use within a given catchment. Located on Barbados’ West Coast, Speightstown and the surrounding areas encompass a well-developed tourist, residential and agricultural area. The main water resource for this area, and the rest of the island, is that of groundwater. The availability of groundwater in Barbados may be adversely affected by the projected changes in climate, such as reduced wet season rainfall. Economic development and changing sector priorities together with climate related changes have the potential to affect water resource abundance and by extension the allocation of resources for example in the Speightstown area. In order to investigate the potential impacts on the Speightstown area specifically, a WEAP Model of the study area was developed to estimate the present available water (baseline reference scenario 2000-2010). From this baseline scenario, it is envisioned that an exploration into projected changes in availability in the near term (2035-2045) and medium/long term (2065-2075) time frames will be undertaken. The generated estimations can assist water managers to better evaluate the status of and identify trends in water use and formulate adaptation measures to offset future deficits.

Keywords: water evaluation and planning system (WEAP), water availability, demand and supply, water allocation

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Mohsin Ali Shaikh, Weiguo Song, Rehmat Karim, Muhammad Kashan Surahio, Muhammad Usman Shahid

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Fire investigations face challenges due to the complexity of fire development, and real-world accidents lack repeatability, making it difficult to apply standardized approaches. The unpredictable nature of fires and the unique conditions of each incident contribute to the complexity, requiring innovative methods and tools for effective analysis and reconstruction. This study proposes to provide the modern accident analysis model through numerical reconstruction for fire investigation in textile buildings. This method employs computer simulation to enhance the overall effectiveness of textile-building investigations. The materials and evidence collected from past incidents reconstruct fire occurrences, progressions, and catastrophic processes. The approach is demonstrated through a case study involving a tragic textile factory fire in Karachi, Pakistan, which claimed 257 lives. The reconstruction method proves invaluable for determining fire origins, assessing losses, establishing accountability, and, significantly, providing preventive insights for complex fire incidents.

Keywords: fire investigation, numerical simulation, fire safety, fire incident, textile building

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Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

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Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

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Authors: Alexander Cho, Harsho Sanyal, Joseph Cataldo

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A quantitative analysis of the different variables on both the South and North green roofs of the Jacob K. Javits Convention Center was taken to find mathematical relationships between net radiation and evapotranspiration (ET), average outside temperature, and the lysimeter weight. Groups of datasets were analyzed, and the relationships were plotted on linear and semi-log graphs to find consistent relationships. Antecedent conditions for each rainstorm were also recorded and plotted against the volumetric water difference within the lysimeter. The first relation was the inverse parabolic relationship between the lysimeter weight and the net radiation and ET. The peaks and valleys of the lysimeter weight corresponded to valleys and peaks in the net radiation and ET respectively, with the 8/22/15 and 1/22/16 datasets showing this trend. The U-shaped and inverse U-shaped plots of the two variables coincided, indicating an inverse relationship between the two variables. Cross variable relationships were examined through graphs with lysimeter weight as the dependent variable on the y-axis. 10 out of 16 of the plots of lysimeter weight vs. outside temperature plots had R² values > 0.9. Antecedent conditions were also recorded for rainstorms, categorized by the amount of precipitation accumulating during the storm. Plotted against the change in the volumetric water weight difference within the lysimeter, a logarithmic regression was found with large R² values. The datasets were compared using the Mann Whitney U-test to see if the datasets were statistically different, using a significance level of 5%; all datasets compared showed a U test statistic value, proving the null hypothesis of the datasets being different from being true.

Keywords: green roof, green infrastructure, Javits Center, evapotranspiration, net radiation, lysimeter

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: automotive flows, flame propagation, combustion modelling, CNG

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Authors: Randolf Von N. Salindo

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The study was conducted to measure the logistics integration capabilities of selected companies in the Bahrain construction industry using the Supply Chain 2000 framework; and, determine the extent and direction of influence of these logistics capabilities and integration competencies on the supply chain performance of the firm. A total of 50 executive respondents (from supervisor to managing director level) from 22 construction and construction supplier firms participated in the study from September to November 2014. The results reveal that respondent Bahraini construction firms have significantly lower levels of logistics capabilities, but higher levels of logistics integration competencies compared to international benchmarks. Using stepwise multiple regression analysis, eight logistics capabilities of Bahraini constructions firms were identified to be positively associated with firm performance; with comprehensive metrics as the most positively dominant influential logistics capability. Activity based and total cost methodology is found to be the most negatively dominant influential logistics capability. In terms of logistics integration competencies, the study revealed that that customer integration, internal integration, and, measurement integration are negatively associated with firm performance. There was no logistics integration competency found to be positively associated with the supply chain performance among the companies who participated in the study. The research reveals that there are areas for improvement in supply chain capabilities and logistics integration competencies of the construction firms in the Kingdom of Bahrain to improve their supply chain performance to a global level.

Keywords: comprehensive metrics, customer integration, logistics integration capabilities, logistics integration competencies

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Authors: Rylle Evan Gabriel Zamora, Micah Dennise Malia, Abygail Deniese Villabona

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The primary motivators of altruism are usually viewed as mutually exclusive. In this study, we wanted to know if the two primary motivators, reciprocity and empathy, can work together in motivating altruism. Therefore, we wanted to find out if there is a significant interaction of effects between reciprocity and empathy. To show how this may occur, we devised the combined altruism model, which is based on Batson’s empathy altruism hypothesis. A sample of 120, 6th-grade students were randomly selected and then randomly assigned to four treatment groups. A 2x2 between subjects’ design was used, which had empathy and reciprocity as independent variables, and altruism as the dependent variable. The study made use of materials that were effort based, where subjects were required to complete a task or a puzzle to help a person in a given scenario, two videos, one to prime empathy were also used. This along with Witt & Boleman’s adapted Self-Reported Altruism Scale was used to determine an individual’s altruism. It was found that both variables were significant in motivating altruism, with empathy being the greater of the two. However, there was no significant interaction of effects between the two variables. To explain why this occurred, we turned to the combined altruism model, where it was found that when empathically primed, we tend to not think of ourselves when helping others. Future studies could focus on other variables, especially age which is said to be one of the greatest factors that influenced the results of the experiment.

Keywords: reciprocity, empathy, altruism, experimental psychology, social psychology

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Authors: Yung-Feng Yen, Yun-Ju Lai

Abstract:

Background: Animal studies have shown that alcohol exposure may cause immunosuppression and increase the susceptibility to tuberculosis (TB) infection. However, the temporality of alcohol consumption with subsequent TB development remains unclear. This nationwide population-based cohort study aimed to investigate the impact of alcohol exposure on TB development in Taiwanese adults. Methods: We included 46 196 adult participants from three rounds (2001, 2005, 2009) of the Taiwan National Health Interview Survey. Alcohol consumption was classified into heavy, regular, social, or never alcohol use. Heavy alcohol consumption was defined as intoxication at least once/week. Alcohol consumption and other covariates were collected by in-person interviews at baseline. Incident cases of active TB were identified from the National Health Insurance database. Multivariate logistic regression was used to estimate the association between alcohol consumption and active TB, with adjustment for age, sex, smoking, socioeconomic status, and other covariates. Results: A total of 279 new cases of active TB occurred during the study follow-up period. Heavy (adjusted odds ratio [AOR], 5.21; 95% confident interval [CI], 2.41-11.26) and regular alcohol use (AOR, 1.73; 95% CI, 1.26-2.38) were associated with higher risks of incident TB after adjusting for the subject demographics and comorbidities. Moreover, a strong dose-response effect was observed between increasing alcohol consumption and incident TB (AOR, 2.26; 95% CI, 1.59-3.21; P <.001). Conclusion: Heavy and regular alcohol consumption were associated with higher risks of active TB. Future TB control programs should consider strategies to lower the overall level of alcohol consumption to reduce the TB disease burden.

Keywords: alcohol consumption, tuberculosis, risk factor, cohort study

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Authors: Jonghyuk Yoon, Hyoungwoon Song

Abstract:

Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

Abstract:

In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

Abstract:

With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

Abstract:

In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Inese Trusina, Elita Jermolajeva, Viktors Gopejenko, Viktor Abramov

Abstract:

Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the development of the way to social well-being in the frame of the ecological economics paradigm. The objective of the article is to present the results of the analysis of socio-economic systems in the context of sustainable development using the systems power (energy flows) changes analyzing method and structural Kaldor's model of GDP. In accordance with the principles of life's development and the ecological concept was formalized the tasks of sustainable development of the open, non-equilibrium, stable socio-economic systems were formalized using the energy flows analysis method. The methodology of monitoring sustainable development and level of life were considered during the research of interactions in the system ‘human - society - nature’ and using the theory of a unified system of space-time measurements. Based on the results of the analysis, the time series consumption energy and economic structural model were formulated for the level, degree and tendencies of sustainable development of the system and formalized the conditions of growth, degrowth and stationarity. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. During the research, the authors calculated and used a system of universal indicators of sustainable development in the invariant coordinate system in energy units. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. In the context of the proposed approach and methods, universal sustainable development indicators were calculated as models of development for the USA and China. The calculations used data from the World Bank database for the period from 1960 to 2019. Main results: 1) In accordance with the proposed approach, the heterogeneous energy resources of countries were reduced to universal power units, summarized and expressed as a unified number. 2) The values of universal indicators of the life’s level were obtained and compared with generally accepted similar indicators.3) The system of indicators in accordance with the requirements of sustainable development can be considered as a basis for monitoring development trends. This work can make a significant contribution to overcoming the difficulties of forming socio-economic policy, which is largely due to the lack of information that allows one to have an idea of the course and trends of socio-economic processes. The existing methods for the monitoring of the change do not fully meet this requirement since indicators have different units of measurement from different areas and, as a rule, are the reaction of socio-economic systems to actions already taken and, moreover, with a time shift. Currently, the inconsistency or inconsistency of measures of heterogeneous social, economic, environmental, and other systems is the reason that social systems are managed in isolation from the general laws of living systems, which can ultimately lead to a systemic crisis.

Keywords: sustainability, system dynamic, power, energy flows, development

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